Method and apparatus for adaptively controlling signals

ABSTRACT

A signal processing system according to various aspects of the present invention includes an excursion signal generator, a scaling system and a filter system. The excursion signal generator identifies a peak portion of a signal that exceeds a threshold and generates a corresponding excursion signal. The scaling system applies a real scale factor to contiguous sets of excursion samples in order to optimize peak-reduction performance. The filter system filters the excursion signal to remove unwanted frequency components from the excursion signal. The filtered excursion signal may then be subtracted from a delayed version of the original signal to reduce the peak. The signal processing system may also control power consumption by adjusting the threshold. The signal processing system may additionally adjust the scale of the excursion signal and/or individual channel signals, such as to meet constraints on channel noise and output spectrum, or to optimize peak reduction. The magnitude threshold, excursion signal and/or individual channel signals may also be adaptively adjusted based on, for example, a channel signal quality such as a noise level specification.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional of application Ser. No. 11/417,477,filed Apr. 27, 2006 now U.S. Pat. No. 7,783,260 to which priority under35 U.S.C. §120 is claimed, the entire contents of which are incorporatedherein by reference.

FIELD OF INVENTION

This invention relates generally to signal transmission systems,including those associated with cellular infrastructure, where signalpeaks may be advantageously reduced, and more particularly to a methodand apparatus for reduction of peak power requirements by adaptivelycontrolling signals.

BACKGROUND OF THE INVENTION

Wireless communication basestations, networks, and other systems usepower amplifiers to transmit signals to cellular phones, handheldmessaging devices, computers, personal electronic assistants, and otherdevices. A power amplifier increases the average power of thetransmitted wireless signal sufficiently to maintain a reliablecommunication link at any required distance. This is necessary becausesignal waveforms are used to efficiently convey information between atransmitter and a distant receiver. Since noise and interference arecombined with the signal waveform at the receiver, the transmitter mustamplify its waveform prior to transmission sufficiently to guaranteethat the ratio of received signal energy to noise/interference energyexceeds a specified value; otherwise the receiver's additivenoise/interference can overwhelm the signal energy, resulting in loss ofinformation over the data link. This constraint applies to communicationsystems employing wireless transmission, including radio frequency (RF),optical and audio technologies.

Pre-transmission amplification of the information-bearing signalwaveform constitutes one of the major costs associated with moderninformation transfer. FIG. 1 depicts a typical relationship betweenamplification cost and the maximum (peak) magnitude of the signalwaveform. Package cost generally dominates for low peak-poweramplifiers. However, beyond some point, additional peak-power capabilityresults in exponentially-increasing amplifier costs. For this reason,signal processing techniques capable of reducing peak values of thetransmitted waveform are greatly valued in modern wireless signaltransmission systems.

The transmitted signal's power varies depending on both the modulationtype and the data sequence being transmitted, which results in peaks andtroughs in the instantaneous power as a function of time. The complexityand cost of an amplifier is highly dependent on the maximuminstantaneous power it must accommodate. Consequently, basestationproviders and operators and other electronics users seek ways to lowerthe instantaneous or “peak” power requirements of the relevant system.

To reduce system peak power requirements, a provider may simply limitthe maximum amplifier output power by constraining or “clipping” themaximum magnitude of the amplifier's output signal. Clipping theamplifier output effectively reduces the peak power output requirementwhile still providing ordinary amplification for non-peak signals. Sincethe cost of a power amplifier rapidly increases as it is required toaccommodate higher peak power levels, clipping can significantly reducesystem cost. Clipping may be particularly attractive in applications inwhich large peaks occur only occasionally. For example, a singleamplifier often simultaneously amplifies signals for multiple channels.Occasionally, the multiple channel signals constructively combine togenerate a relatively high peak. The amplifier must either fully amplifythe peak, requiring an expensive high peak-power amplifier, or theoutput magnitude may be clipped to facilitate the use of a lowerpeak-power, less expensive amplifier.

In wireless communications and networking, however, clipping isunacceptable. Clipping induces spectral regrowth, creating spectralenergy in potentially restricted spectral regions. The electromagneticspectrum is a finite resource, and it is strictly apportioned byrestrictions from various governmental regulating agencies to minimizeinterference from competing users. The various spectrum users receivepermission to transmit within certain bandwidths and are ordinarilyprohibited from transmitting outside of the designated bandwidth. Evenwithin the so-called “unlicensed bands”, strict FCC standards regulatespectral emissions to minimize interferences. Because spectral regrowthadds unacceptable frequency components to the signal, spectrumregulations do not permit clipping as a solution for high-poweramplifier requirements.

The relationship between signal peaks and amplifier characteristics isof great significance with respect to wireless communications. Efficientpower amplifiers exhibit an intrinsically nonlinear relationship betweeninput and output power. The relationship between amplifier input andoutput power is depicted in the lower curve 240 of FIG. 2. For lowlevels of input power, the amplifier output signal is essentially alinearly-amplified replica of the input. However, at higher input signalpower levels, the amplifier output reaches an upper limit, the amplifiersaturation power, which cannot be exceeded. The region of the amplifiercurve near the saturation point is nonlinear. Operation of the amplifiernear its nonlinear amplification region generates unacceptable nonlinearnoise which violates regulatory spectral masks, forcing operation at alower input power level. Prior art includes numerous techniques whichcan be used to ‘linearize’ an amplifier, thus mitigating the nonlinearcharacteristic, and approaching the ideal linear relationship shown inthe upper curve 242 in FIG. 2.

Amplifier nonlinearities convert input signal energy into nonlinearspectral energy which may violate regulatory spectral mask constraints.It is therefore necessary to limit the strength of the signal input tothe amplifier so that its magnitude only rarely extends beyond thelinear region of operation. As FIG. 2 shows, the value of amplifierlinearization is that it can greatly extend the upper limits of theamplifier's linear region. After the amplifier has been linearized tothe practical limit, generation of unwanted nonlinear spectralcomponents may be further reduced by limiting the likelihood that thesignal magnitude extends beyond the amplifier's linear region. Thisreflects the important fact that generation of unwanted nonlinearcomponents requires that signal peaks extend beyond the amplifier'slinear region; both signal and amplifier characteristics are involved,and both must be addressed.

The need for peak-reduction processing was greatly increased by therelatively recent widespread adoption of so-called ‘multi-channel’signal waveforms for wireless infrastructure systems. The adoption ofmulti-channel signaling (MCS) occurred because of the strong economicincentive to combine several independent signal waveforms wherein all ofthe signals are transmitted in the same spatial direction and allsignals can then share a single antenna. Previously, infrastructurebasestations separately amplified each waveform, which were thencombined using a ‘diplexer’ before sending the composite amplifiedsignal to the antenna. However, since a four-signal high-power diplexercan cost on the order of $10,000, an alternative solution in the form ofMCS was developed. In MCS, several independent signal waveforms aregenerated and combined while still in digital form. The combined signalsthen share a common frequency translation to RF, a common amplifier anda common antenna. The heavy, bulky, and expensive diplexer iseliminated. The digital channel waveforms remain separated by theinter-channel frequency spacing, typically less than ten megahertz, sothat inexpensive (relatively low rate) digital processing can easilygenerate the composite waveform. FIG. 3 depicts the baseband complexspectra associated with four adjacent cellular signals. Note that thefrequency offsets correspond only to the relative transmissionfrequencies, since the common RF frequency translation will be added tothe MCS waveform after it has been converted into analog form. While MCSprovides an economically advantageous solution to the diplexer problemassociated with earlier transmission systems, MCS greatly aggravates thepeak magnitude problem, since the signal peak of an MCS waveform is muchhigher than that of each of its component signal waveforms. Thus, MCSremains an incomplete solution to the diplexer problem of earliertransmission systems until peak reduction in MCS is effectivelyaddressed.

In addition to the emergence of MCS waveforms with their large peakmagnitudes, several important worldwide wireless standards [e.g. 802.11(WiFi) and 802.16 (WiMAX)] have adopted orthogonal frequency-divisionmultiplexing (OFDM) waveforms which use parallel transmission of manynarrowband components. An OFDM signal may be considered as a specialcase of multi-channel transmission, with no spectral spacing betweenadjacent channels, and short burst (rather than continuous)transmission. The WiMAX waveform, which has been proposed as a potentialworldwide solution for all wireless communication, uses basestationtransmissions consisting of OFDM with several hundred channels. Thesechannels are allocated to many users, with modulation types and powerlevels of those sets of channels sent to each user selected based on thepath attenuation for each distinct physical link. The large peak powerlevel variation of the many OFDM channels generates peak-reductiondemands similar to those of MCS. OFDM must also satisfy stringent errorvector magnitude (EVM) constraints for each set of channels allocatedfor each individual user, in the face of dynamically-varying channelmodulation orders, path losses, and signal power levels. Peak-reductionprocessing therefore offers economic advantages to modern wirelesscommunication systems, both RF and optical, both MCS and OFDM, as wellas any other system in which signal peaks are beneficially reduced basedon any standard, requirement or economic factor including, for example,digital radio and television broadcast systems.

Numerous technical papers directed to techniques for peak-reductionprocessing have been published, and several patents have been awarded,as would be expected for such an economically vital challenge.

One peak-reduction processing approach simply modifies the informationstream itself prior to the signal generation (modulation) operation.See, e.g., R. W. Bauml, R. F. H. Fisher, and J. B. Huber, “Reducing thePeak-to-Average Power Ratio of Multi-Carrier Modulation by SelectedMapping,” Electron. Lett., vol. 32, no. 22, October 1996, pp. 2056-2057;R. van Nee and A. de Wild, “Reducing the Peak-to-Average Power Ratio ofOFDM,” Proc. IEEE VTC '98, May 1998, pp. 2072-2076. While this techniquereduces the peaks, it also significantly degrades the performance oferror-correction coding, and has thus failed to find any significantmarket acceptance.

Other approaches generate/modulate the information stream onto thewaveform, then alter that waveform to reduce its peak magnitude. See,e.g., T. May and H. Rohling, “Reducing the Peak-To-Average Power Ratioin OFDM Radio Transmission Systems,” Proc. IEEE VTC '98, May 1998, pp.2474-78. One such approach applies localized smoothly-varyingattenuation to the signal in the vicinity of each peak. Yet anotherapproach avoids generating nonlinear noise by simply subtractingsuitably scaled band-limited pulses from the signal to cancel each peak.While these approaches offer improvement, and at least two patents (U.S.Pat. Nos. 6,366,319 and 6,104,761) have been granted for such anapproach, they both add excessive noise to the signal. These approachesalso do not offer a comprehensive and systematic peak-reductionprocessing solution when the MCS channels are dynamically varying inrelative power levels and when the EVM requirements of each channel alsodynamically vary, as is the case with real-world MCS transmission.

Still another technique is the classic clip-and-filter approach, whichsimply passes the waveform through a “clipper” (i.e. hard-limiter), thenfilters the clipped to ensure compliance with regulatory spectralconstraints. This approach is very commonly used for peak-reduction ofOFDM signals. e.g., R. O'Neill and L. Lopes, “Envelope Variations andSpectral Splatter in Clipped Multi-carrier Signals,” Proceedings of thePMRC '95, September 1995, pp. 71-75; J. Armstrong, “New OFDMPeak-to-Average Power Reduction Scheme,” IEEE VTC 2001, May 2001,Rhodes, Greece; J. Armstrong, “Peak-to-Average Power Reduction inDigital Television Transmitters,” DICTA2002 Conference, Melbourne,January 2002, pp. 19-24; J. Armstrong, “Peak-to-Average Power Reductionfor OFDM by Repeated Clipping and Frequency Domain Filtering,”Electronics Letters. vol. 38, No. 5, February 2002, pp. 246-47; U.S.Patent Publication Nos. 2004/0266372, 2004/0266369; H. A. Suraweera, K.Panta, M. Feramez and J. Armstrong, “OFDM Peak-to-Average PowerReduction Scheme With Spectral Masking,” Int'l Symposium on Comm.Systems Networks and Digital Processing (2004). The prior art in thisarea does nothing more than filter away out-of-band (OOB) energy.However, hard-limiting in this manner introduces passband nonlinearinterference which cannot be removed by out-of-band filtering, and evenout-of-band DFT filtering distorts the signal.

A conceptually-related peak reduction technique involves determining the‘excursion’ (the portion of the signal exceeding a defined magnitudethreshold), then filtering, scaling and time-aligning the excursionprior to subtracting it from a suitably delayed version of the originalsignal. This ‘filtered excursion’ approach eliminates signal distortionby applying filtering only to the excursion. The advantage is thatspectral constraints are met without generating signal distortion, andpeaks can be reduced by the maximum amount permitted by spectralconstraints. The only prior art description of the filtered excursionapproach, J. Armstrong, “PCC-OFDM with Reduced Peak-to-Average PowerRatio,” in IEEE 3Gwireless 2001, May 30-Jun. 2, 2001, San Francisco, pp.386-391, is limited to a non-standard variant of OFDM that involvesoverlapped symbols. The author has notably described clip-and-filter asthe preferred peak-reduction approach for standard OFDM signals in allsubsequent publications.

This ‘filtered excursion’ approach forms the theoretical basis for thepresent invention as described and claimed below, but the presentinvention goes beyond prior approaches in several significant respects.The prior art relating to the filtered excursion approach topeak-reduction processing properly recognized the need for interpolationprior to forming the excursion signal, although claiming, incorrectly,that over-sampling by a factor of only two was required. An increasedsampling rate prevents nonlinear spectral components associated with theexcursion from aliasing back into the spectrum occupied by the originalsignal. This is important because once such nonlinear components occur,they cannot be removed by filtering. However, the prior art failed torecognize several critical factors involved in achieving optimal peakreduction. For example, the prior art did not recognize the need to varythe attenuation-versus-frequency characteristic of the excursionfiltering across the signal passband in order to properly protect theweaker signal components. The prior art described only staticfrequency-dependent attenuation of the out-of-band excursion spectralcomponents, and pointedly instructed to “distort the in-band (i.e.passband) component of the difference (excursion) as little aspossible.” However, the nonlinearity represented by excursion formationgenerates relatively uniform spectral nonlinearity noise across thesignal bandwidth. Ensuring that all portions of the signal satisfy aminimal signal-to-noise ratio (SNR) constraint thus requires that extraattenuation be applied to the excursion in those spectral regions ofweaker signal spectral energy. Even more critically, since the relativespectral energy of different signals varies dynamically, any suchsignal-responsive filtering must be dynamically adapted over time.Finally, each portion of a multi-channel signal must independentlysatisfy the error vector magnitude (EVM) constraint, which limits eachdistinct channel's SNR to one of a set of defined values, depending onthat channel's modulation type. The cited prior art failed to recognizethe need to dynamically adapt the signal passband ‘filtering’ in orderto satisfy this critical specification. Finally, the prior art failed tograsp the critical importance of applying dynamic scaling to differentportions of the excursion prior to filtering in order to achievesignificantly enhanced peak-reduction. An object of the presentinvention is thus to provide gain and other control strategies foroptimizing peak reduction subject to noise level (for example EVM)constraints, signal dynamics and residual linear and nonlineardistortion energy considerations.

SUMMARY OF THE INVENTION

A signal processing system for use in, for example, a communicationand/or amplifier system, according to various aspects of the presentinvention includes an excursion signal generator and a filter system.The excursion signal generator identifies a peak portion of a signalexceeding a threshold, such as a magnitude threshold. Distinct portionsof the excursion waveform are dynamically scaled to enhance peakreduction. The filter system filters a corresponding excursion signalhaving a magnitude and waveform corresponding to the portion exceedingthe threshold to remove unwanted frequency components from a scaledversion of the excursion signal. The filtered excursion signal may thenbe subtracted from a delayed version of the original signal to reducethe peak. In one embodiment, the signal processing system adapts tovarying channel power levels by adjusting the magnitude threshold. Thesignal processing system may also adjust the scale of the excursionsignal and/or individual channel signals, such as to meet constraints onchannel noise and output spectrum, or to optimize peak reduction. Inother embodiments, the magnitude threshold, excursion signal and/orindividual channel signals may also be adaptively adjusted based on, forexample, a channel signal quality such as a noise level specification.

BRIEF DESCRIPTION OF THE DRAWING FIGURES

A more complete understanding of the present invention may be derived byreferring to the detailed description when considered in connection withthe following illustrative figures. In the following figures, likereference numbers refer to similar elements and steps.

FIG. 1 illustrates the relationship between the magnitude of the signalpeak and amplifier cost;

FIG. 2 is a comparison of nonlinear and linearized amplifiercharacteristics;

FIG. 3 shows the baseband complex spectra associated with adjacentcellular signals;

FIG. 4 is an illustration of a complex signal over time and a magnitudethreshold;

FIG. 5 shows an exemplary signal magnitude probability density function(pdf);

FIG. 6 shows an exemplary peak-reduced signal magnitude probabilitydensity function;

FIG. 7 depicts complementary cumulative distribution function (CCDF)curves corresponding to four wideband code-division multiple access(WCDMA) channels using various values for the magnitude threshold;

FIG. 8 shows an optimized relationship between peak-reduction andamplifier linearization;

FIG. 9 shows exemplary raw excursion and filtered excursion waveformsincluding a portion of a signal exceeding a defined threshold;

FIG. 10 is a diagram of an excursion comprising multiple peaks or “peakevents”;

FIG. 11 is a block diagram of a communications system according tovarious aspects of the present invention;

FIG. 12 is a block diagram of a signal processing system having apeak-power reduction component according to various aspects of thepresent invention;

FIG. 13 is a block diagram of an MCS modulator;

FIG. 14 is a block diagram of a peak-power reduction component;

FIG. 15 is a block diagram of an alternative embodiment of an excursionsignal generator;

FIG. 16 is a block diagram of an embodiment of an excursion signalgenerator;

FIG. 17 is a block diagram of an excursion signal generator havingmultiple scaling circuits;

FIG. 18 A-C are frequency diagrams for a signal processed by a filtersystem;

FIG. 19 is a diagram of a channel filter for filtering subchannels;

FIG. 20 is a magnitude diagram of a signal comprising multiple channelshaving subchannels;

FIG. 21 is a schematic of a detailed peak-reduction processing algorithmand architecture including an exemplary channel scaling circuit;

FIG. 22 illustrates a peak-reduction processing architecture;

FIG. 23 is a schematic of a detailed peak-reduction processing algorithmand architecture including an exemplary channel scaling circuit andcircuitry for adaptively varying the signal magnitude threshold;

FIG. 24 shows a functional architecture for a typical excursion filtersystem 514;

FIG. 25 is a schematic representation of an excursion filter, acorresponding scaling filter, and their respective impulse responses;

FIG. 26 is a plot describing the desired variation in the gain withineach channel filter 518 as a function of the filtered excursion powerfrom each excursion filter channel;

FIG. 27 is an illustrative plot showing gain-controlled EVM dynamicscorresponding to the algorithm and architecture of FIG. 21;

FIG. 27A is an illustrative plot showing the negligible spectral impactof EVM-controlled gain using the algorithm and architecture of FIG. 21;

FIG. 27B shows a raw and peak-reduced CCDF plot for a combination offour strong channels corresponding to the algorithm and architecture ofFIG. 23;

FIG. 27C shows a plot of channel gains and EVM values versus timecorresponding to the CCDF plot of FIG. 27B;

FIG. 27D shows a raw and peak-reduced CCDF plot for one weak channel andthree strong channels corresponding to the algorithm and architecture ofFIG. 23;

FIG. 27E shows a plot of channel gains and EVM values versus timecorresponding to the CCDF plot of FIG. 27D;

FIG. 27F shows an improved CCDF plot achieved using cascaded peakreduction;

FIG. 28 is a block diagram of a scaling system having anapproximation/scaling filter;

FIG. 29 is a TDMA waveform diagram of a sequence of time slots and atime slot windowing signal;

FIG. 30 is a block diagram of a filter system having additional filtersand a switching system;

FIG. 31 shows the magnitude of a TDMA signal comprising multiplechannels transmitted in a series of time slots;

FIG. 32 is a block diagram of an OFDM peak-power reduction componenthaving an interpolator, a decimator, fast Fourier transforms (FFTs), andpeak-event scaling, that shows mask generation based on channel-specificsignal power and EVM constraints; and

FIG. 33 is a block diagram of an OFDM peak-power reduction componenthaving an interpolator, a decimator, fast Fourier transforms (FFTs),peak-event scaling, mask generation based on channel-specific signalpower and EVM constraints, and adaptive control of the magnitudethreshold.

Elements and steps in the figures are illustrated for simplicity andclarity and have not necessarily been rendered according to anyparticular sequence. For example, steps that may be performedconcurrently or in different order are illustrated in the figures tohelp to improve understanding of embodiments of the present invention.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

The peak-reduction concepts of the present invention as discussed beloware presented primarily in the context of MCS (typically four WCDMAchannels), since it simplifies the discussion to treat a smaller numberof signal channels. However, the peak-reduction processing concepts ofthe present invention are equally applicable to OFDM signals. Similarly,the discussion below is presented in the context of wirelesscommunications systems. However, the peak-reduction processing conceptsof the present invention are equally applicable to, for example, digitalradio and television broadcast systems, including wired, terrestrial andsatellite broadcast systems. The invention may, for example, providebenefits in the processing of any signal conveyed via variations inelectromagnetic or acoustic fields. The inventive concepts may thereforebe applied in optical data transmission and audio systems. The presentinvention thus includes within its scope the processing of signals, orapparatus therefor, in any system in which signal peaks may beadvantageously reduced based on or pursuant to any standard, requirementor economic factor.

In the following discussion of the peak-reduction concepts of thepresent invention, the signal is assumed to be represented by a sequenceof complex (i.e. quadrature) samples that uniquely describe the signal'sinstantaneous magnitude and phase as these values dynamically evolveover time. The random information borne by the signal results in randomdynamic variations in signal phase and magnitude. FIG. 4 depicts such asignal as a time-varying trajectory. The cylindrical surface feature inFIG. 4 simply corresponds to a defined constraint on signal magnitude(the ‘threshold’). Occasionally, the magnitude exceeds the threshold; inFIG. 4 the extra-cylinder portion 410 of the signal 222 is illustrativeof the portion of the signal which exceeds the threshold 412.

With reference to FIG. 4, the ‘clipped signal’ is that portion of thesignal lying entirely within, or on, the cylinder, with the portionexterior to the cylinder replaced by its projection 410A onto thecylinder. The clipped signal magnitude is bounded by the thresholdvalue; its phase is always identical to the original (unclipped) signal.This constraint on signal magnitude can be expressed mathematically asfollows:

${C(n)} \equiv \begin{matrix}{S(n)} & {\forall_{n}{{\_{{S(n)}}} \leq M}} \\{M\lbrack \frac{S(n)}{{S(n)}} \rbrack} & {\forall_{n}{{\_{{S(n)}}} > M}}\end{matrix}$Where C(n) is the clipped signal, S(n) is the unclipped signal, ∥S(n)∥is the magnitude of the unclipped signal, M is the magnitude thresholdand ∀_(n) _(—) ∥S(n)∥ means “for all values of n such that the magnitudeof S(n).” Each signal segment 410 outside the cylindrical surface isdefined as an excursion event X(n):X(n)≡S(n)−C(n)

Variation in signal magnitude can be quantified statistically. FIG. 5 isa schematic representation of the so-called magnitude probabilitydensity function (pdf) for a typical signal. Note that the magnitude pdf250 exhibits a very long tail (along the Signal Magnitude axis),implying that very large values of signal magnitude can occur, albeitwith declining likelihood as the signal magnitude gets larger. Thepurpose of peak-reduction processing is to alter the signal in a mannerwhich eliminates or substantially reduces the probability that thesignal magnitude will exceed some defined (threshold) value. To totallyeliminate the possibility that the signal magnitude will exceed such athreshold value would have the effect of modifying the magnitude pdffrom that depicted in FIG. 5 to that depicted in FIG. 6. The verticaldashed line 412 of FIG. 5 represents the magnitude threshold value. Theincrease in probability near the magnitude threshold in FIG. 6 ascompared to FIG. 5 is a result of the fact that the area under the pdfcurve must equal unity. The impact of a peak-reduction algorithm musttherefore be able to transfer the tail (above the magnitude threshold)back into the body of the pdf (below the magnitude threshold). MCSmagnitude pdfs exhibit extremely long tails like that shown in FIG. 5,which illustrates why MCS remains an incomplete solution to the diplexerproblem discussed above until peak-reduction is effectively addressed.

Therefore, as can be appreciated from FIGS. 5 and 6, an importantfunction of peak-reduction processing is to reduce the likelihood oflarge signal magnitudes. The communications industry commonly uses thestatistical metric known as the Complementary Cumulative ProbabilityDensity Function (CCDF) plot to more clearly characterize theeffectiveness of peak-reduction processing. The x-axis (horizontal) of aCCDF curve begins at 0 dB (defined as the average power of the signal),and extends to the maximum peak-to-average power ratio (PAR) value ofthe signal. The y-axis (vertical) of a CCDF curve lists the probability(on a log scale) that a given complex sample has any specificpeak-to-average value. Plotting the before and after CCDF curves on thesame graph characterizes the effectiveness of peak reduction. PlottingCCDFs for the same signal set using alternative peak-reductionprocessing algorithms clearly describes their comparative effectiveness.For example, FIG. 7 depicts CCDFs corresponding to four peak-reducedWCDMA channels using various values for the magnitude threshold M. InFIG. 7 the right-most curve corresponds to the raw input and the othercurves correspond to the peak-reduced channel signals.

As discussed above with respect to prior art attempts to solve theproblems associated with peak-power reduction, in the absence ofregulatory spectral constraints, the optimal peak-reduction approachwould be to simply determine the excursion and subtract that waveformfrom the original signal. This would yield the clipped signal. However,a spectral mask constraint does in fact exist, e.g., in the wirelesstelecommunications field, and therefore the original signal must bedesigned to satisfy the spectral mask. Thus, since the original signalin such a system is designed to satisfy the spectral mask constraint,only the excursion contributes unacceptable spectral energy. Sufficientfiltering must therefore be applied to the excursion waveform(consisting of many isolated excursion events), to achieve compliancewith the regulatory spectral masks. While this approach will not achievecomplete cancellation of the deleterious excursion events, it comes asclose as possible within the constraints of such a filtering techniquewhile complying with the regulatory spectral constraints. Thepeak-reduction approach described and claimed herein builds on such a“filtered excursion” concept to provide a more complete solution to theproblems associated with peak-reduction processing.

It is readily apparent that the signal magnitude probability densityfunction as depicted in FIGS. 5 and 6 can be altered simply by replacingthe original signal by the clipped signal, as defined above.Unfortunately, as also discussed above, clipping is an intrinsicallynonlinear operation which introduces abrupt discontinuities inhigher-order signal derivatives. Such discontinuities result inso-called spectral splatter, which generates spurious spectral energyoutside the regulatory spectral mask. There is thus a need tosimultaneously satisfy the spectral mask and re-shape the magnitudeprobability density function. Various aspects of the approach of thepresent peak-reduction concept achieve this and other objectives.

With respect to the discussion of variation in signal magnitude abovewith respect to FIGS. 2, 5 and 6, note that peak reduction will permitthe signal to enter the amplifier shifted further to the right whetheror not linearization is used. If both peak reduction and linearizationare used, the signal input power level may be increased (i.e. shifted tothe right) so that the signal magnitude threshold is identical to theupper limit of the amplifier linear region. This yields the maximumaverage output power and operating efficiency possible with a particularsignal and amplifier. A signal transmission system may employ both theseprocessing techniques, offering unique synergistic benefits. FIG. 8depicts a peak-reduced signal at two different input powers with respectto a linearized amplifier characteristic 242. In both cases, theamplifier operation is entirely linear, since the entire signalmagnitude range lies within the amplifier's linear region of operation.However, the amplifier output power is greater when the input signal hasbeen pre-amplified, which shifts the pdf curve 252 so that its magnitudepeak aligns with the amplifier's maximum linear limit, as illustrated bythe right-most magnitude pdf curve 254.

FIG. 8 graphically depicts the key relationships between peak reductionand amplifier linearization. An objective of the present invention is tominimize the signal's maximum PAR value, the vertical boundary ideallyto be aligned with the maximum linear limit of the amplifier. Forexample, every 1 dB reduction in PAR increases the maximum averageamplifier power output by an extra 1 dB. A 3 dB reduction in signal PARcan reduce the cost of a basestation amplifier by thousands of dollars,providing a significant economic incentive.

FIG. 9 depicts a portion of a signal segment showing magnitude as itexceeds a defined threshold 412, the corresponding excursion event 410and the filtered excursion 410B. The broad shaded bands representpre-cursor 412A and post-cursor 412B segments, in whichexponentially-decaying oscillations occur. Note that as the excursionfilter system smoothes the excursion waveform it alters the peakmagnitude from what is required to completely cancel the peak whensubsequently subtracted from the time-aligned original signal. Eachfiltered excursion must therefore be scaled to ensure that subsequentsubtraction from the time-aligned original signal reduces the signalpeak to match the defined threshold. It is thus apparent that thedesired scale factor is the ratio of the excursion peak magnitude M_(x)to the filtered excursion peak magnitude M_(f). Since the filter'simpact is invariant to scale changes, this scaling ensures that thefiltered peak substantially matches the original excursion peakmagnitude. However, the excursion scaling operation is complicated bythe fact that the optimal scale factor is different for every excursionand depends on a complex interaction (convolution) between excursionsamples and excursion filter system characteristics.

Excursion events are typically comprised of multiple local peak events.The heuristic description above conveys the core concept of filteredexcursions, and the need to scale each excursion by a factor dependingon both the excursion shape and the applied filtering. However, prior todescribing a functional architecture for peak reduction within the scopeof the present invention, the definitions of terms must be extended toaddress the fact that excursion events, consisting of contiguousnon-zero excursion waveform samples, often are comprised of multiplesignal magnitude peaks. FIG. 10 depicts an example of such a multi-peakexcursion event, and shows the manner in which each such excursion event2310 may be partitioned (‘parsed’) into a set of contiguous peak events2312. In this example, the boundary between peak events is defined asthe magnitude sample at the local minimum; it may be arbitrarilyincluded in either of the bordering peak events for purposes of scaling.The scaling procedure may then parse the excursion waveform into sets ofpeak events, determine the optimal scaling factor for the complexsamples which comprise each peak event, and then apply the resultantscaling factor prior to filtering of the excursion signal to satisfyspectral mask constraints. Of course, in other embodiments of thepresent invention excursion events may be parsed differently, based onany characteristics or attribute of the signal excursion which resultsin the desired excursion reduction.

The present invention is described partly in terms of functionalcomponents and partly in terms of various processing steps. Suchfunctional components may be realized by any number of componentsconfigured to perform the specified functions and achieve the variousresults. For example, the present invention may employ various elements,materials, signal sources, signal types, integrated components,amplifiers, filters, and the like, which may carry out a variety offunctions. In addition, although the invention is described in thewireless communication environment, the present invention may bepracticed in conjunction with any number of applications, environments,communication protocols, amplification systems, and signal processingsystems, including, but not limited to, optical/acoustic applications,environments, communication protocols and systems. The systems describedherein are merely exemplary applications for the invention. Further, thepresent invention may employ any number of techniques for manufacturing,assembling, testing, and the like.

Referring to FIG. 11, a communications system 100 according to variousexemplary aspects of the present invention comprises a transmitter 110and a receiver 112. The transmitter 110 provides signals such as opticalsignals, electrical signals, acoustic signals, or any other signal whichmay convey information within the scope of the present invention to thereceiver 112 via a medium 114. The medium 114 may comprise any mechanismfor transmitting information between the transmitter 110 and thereceiver 112. In the present exemplary embodiment directed to a wirelesscommunications system, the transmitter 110 provides electromagneticsignals to the receiver 112, such as radio frequency (RF) signals,wireless telephone signals, or wireless data signals. The medium 114 inthe present embodiment is thus any medium capable of sustainingtransmission of electromagnetic signals.

The transmitter 110 and the receiver 112 are respectively configured totransmit and receive signals transmitted via the medium 114. Thetransmitter 110 and/or the receiver 112 may be configured as atransceiver to allow the reception and transmission of multiple signalsfrom the same unit. In the present embodiment, the transmitter 110 isconfigured to modulate and transmit multiple signals to multiplereceivers 112. This configuration corresponds, to for example, awireless communications basestation. In this embodiment, the receivers112 comprise remote receivers, such as wireless telephones, computers,personal digital assistants, handheld electronic message devices orother such receivers. The communications system 100 may be configured,however, in any suitable manner for communicating between anytransmitter 110 and receiver 112, such as computers in a network, forexample via a wireless network using multi-carrier modulations such asorthogonal frequency division multiplexing (OFDM) or orthogonalfrequency division multiple access (OFDMA).

The transmitter 110 of FIG. 11 may be suitably configured to process adigital signal and transmit a corresponding signal to the receiver 112.In a typical cellular communications embodiment, for example, thetransmitter 110 may be configured in accordance with any appropriatespecifications or standards for wireless digital communication, such asin accordance with Global System for Mobile Communications (GSM), timedivision multiple access (TDMA), and/or code division multiple access(CDMA) specifications or standards. In a data communicationsenvironment, the transmitter 110 may be configured in conjunction withany suitable data communications specification or standard, such as IEEE802.11, 802.15, or 802.16. The transmitter 110 may be further configuredin any suitable manner to receive digital information and transmit acorresponding analog signal to the receiver 112.

For example, referring to FIG. 12, the transmitter 110 of the presentembodiment includes a signal processing system 208 for processing asignal, such as for communication via the communication system 100. Inthe present embodiment, the signal processing system 208 includes amodulator 210, a peak-power reduction component 212, a digital-to-analogconverter (DAC) 214, an RF converter 214A, and an amplifier 216. Themodulator 210 receives digital information 220 from one or more datasources 218 and generates a baseband modulated signal 222.

In various embodiments, the peak-power reduction component 212 isconfigured to receive the modulated signal 222 from the modulator 210and substantially reduce the peak power output requirement of thetransmitter 110. The peak-power reduction component 212 may beadditionally configured to inhibit spectral regrowth or other frequencycomponents outside one or more desired bandwidths. In addition, thepeak-power reduction component 212 may be further configured to inhibitor minimize the addition of noise to the signal to maintain anacceptable signal-to-noise ratio and/or remain within relevant errorvector magnitude (EVM) constraints.

The DAC 214 is configured to receive a peak-reduced digital signal 224from the peak-power reduction component 212 and convert the digitalsignal into an analog signal 226. The RF converter 214A translates theanalog signal from a lower frequency (near or at baseband) to thedesired RF transmission frequency prior to amplification. The amplifier216 amplifies the analog RF signal 228 prior to transmission to thereceiver 112. Additional distortion-compensation processing may beperformed after the peak-power reduction component 212 and prior to theDAC 214.

The modulator 210 may comprise any suitable system for modulating adigital signal. Referring to FIG. 13, an exemplary modulator 210comprises a conventional digital modulator and generates a basebandmodulated multi-channel signal 222. The modulator 210 suitably comprisesa multi-channel modulator for receiving multiple data streams,modulating the data stream for each channel and frequency translatingthe modulated signal to an appropriate offset frequency, and summing thevarious channel outputs into a composite output signal. The modulator210 may be configured, however, in any suitable manner, for example as asingle-channel modulator. The present exemplary modulator 210 comprisesone or more baseband modulators 312 and one or more digital synthesizers314. Each baseband modulator 312A-D converts data into a basebandwaveform according to an appropriate modulation, such that each basebandmodulator 312A-D converts information bits, such as compressed binarydigital data corresponding to voice, data, or video signals, into acorresponding baseband digital waveform 316A-D. The baseband digitalwaveforms 316A-D may comprise any suitable waveforms, such as waveformsin accordance with a selected transmission encoding specification, suchas GSM, spread spectrum, TDMA, CDMA, or the like. In an exemplaryembodiment, the baseband digital waveforms 316A-D comprise time-varyingsequences of complex pairs having an in-phase component (I) and aquadrature component (Q) occurring at a defined sample rate.

In various embodiments, each digital synthesizer 314A-D generates acomplex digital local oscillator (LO) signal that multiplies thebaseband digital waveform to generate offset-frequency modulated signals322, which are then combined to form the baseband multi-channel signal222. The digital synthesizer 314 may comprise any appropriate source ofa digital carrier frequency or other signal to generate the individualoffset-frequency modulated signals 322A-D. In the present exemplaryembodiment, the digital synthesizer 314 comprises a conventionalmultiple-output digital synthesizer configured to provide severaldifferent LO signals 318A-D at different offset frequencies. Thesefrequencies may, for example, correspond to offset frequencies foraccepted transmission frequencies for a particular cellular or wirelessnetwork, or other communication spectral mask. In the present exemplaryembodiment, the digital synthesizer 314 may suitably generatecomplex-exponential (“cisoid”) signals 318A-D at the desired offsetfrequencies for the individual offset-modulated modulated signals 322A-Dfor each channel. In this embodiment of the present invention, thedigital synthesizer output signal 318 is multiplied with the basebanddigital waveform 316 for the relevant channel via a multiplier, thustranslating each baseband waveform to the proper channel offsetfrequency, thus constituting the individual offset-frequency modulatedsignals 322A-D. The various offset-frequency modulated signals 322A-Dmay be summed to form the composite baseband modulated signal 222.

Referring again to FIGS. 11 and 12, in an exemplary embodiment of apeak-power reduction component within the scope of the presentinvention, the composite baseband modulated signal 222 is provided tothe peak-power reduction component 212 from the MCS modulator 210. Thepeak-power reduction component 212 may be configured in any suitablemanner to reduce the peak power output of the transmitter 110, such asby subtracting portions of the signal exceeding a threshold from thesignal. The peak-power reduction component 212 may also inhibittransmission of unwanted spectral energy, for example frequencycomponents outside a regulatory spectral mask. The peak-power reductioncomponent 212 receives the baseband modulated signal 222 from themodulator 210 and processes the baseband modulated signal 222 accordingto any suitable process. For example, referring to FIG. 4, thepeak-power reduction component 212 may be configured to generate anexcursion signal in response to a peak portion 410 in the basebandmodulated signal 222 having a magnitude beyond a defined magnitudethreshold 412. The peak-power reduction component 212 suitably removesor reduces the peak portion 410 from the baseband modulated signal 222in response to the excursion signal.

Referring to FIG. 14, an exemplary embodiment of a peak-power reductioncomponent 212 according to various aspects of the present inventioncomprises a delay element 510, an interpolator 502, an excursion signalgenerator 512, a scaling system 820, an excursion filter system 514, andan excursion reducer 544. The excursion signal generator 512 generatesan excursion signal 410 in response to the baseband modulated signal 222exceeding the magnitude threshold 412 as shown in FIG. 4. The output 410of the excursion signal generator 512 may also be scaled by scalingsystem 820 prior to being processed by the excursion filter system 514.As shown in FIG. 14, the excursion filter system 514 filters unwantedfrequencies from the signals produced by the excursion signal generator512. An excursion reducer 544 subtracts the scaled and filteredexcursion signal from the suitably delayed baseband modulated signal222. The delay element 510 compensates for propagation time delaythrough the excursion signal generator 512 and the excursion filtersystem 514 so that the signal from the filter system 552 is time-alignedwith the delayed baseband modulated signal 222.

The excursion signal generator 512 shown in the peak-power reductioncomponent of FIG. 14 may be configured in any suitable manner togenerate an excursion signal 410 responsive to peak portions of thebaseband modulated signal 222 or other relevant signal. A suitablyscaled and filtered version of the excursion signal 410 may then besubtracted from or otherwise used to reduce one or more peaks in theoriginal signal. Moreover, the excursion signal 410 may be used in anysuitable manner to reduce the peak power of the original signal.Referring to FIG. 15, an exemplary excursion signal generator 512comprises a magnitude calculation circuit 810, a threshold circuit 812(not shown), a peak parser 910 and a waveform generator 814. The output410 of the excursion signal generator 512 is fed into the scaling system820. The peak parser 910 identifies individual magnitude peaks in thesignal 222, and the waveform generator 814 generates the excursionsignal 410 in response to the identified peaks. In one embodiment, theexcursion signal generator 512 receives the baseband modulated signal222 and calculates magnitude values, such as successive magnitude valuesof the baseband modulated signal 222 based on the successive signalcomplex pairs. The excursion signal generator 512 compares the magnitudeof samples of the signal 222 to the magnitude threshold 412. Theexcursion signal generator 512 generates the excursion signal 410 inresponse to the portions of the baseband modulated signal 222 thatexceed the magnitude threshold 412. In yet another exemplary embodiment,the excursion signal generator 512 is configured to generate anexcursion signal 410 that corresponds to the full duration (or full setof samples) of the baseband modulated signal 222 that exceeds themagnitude threshold 412, though the excursion signal generator 512 maybe configured to generate an excursion signal 410 corresponding to anyaspect of the signal exceeding the magnitude threshold 412.

Referring to FIG. 16, an exemplary excursion signal generator 512comprises a magnitude calculation circuit 810, a threshold circuit 812and a waveform generator 814, whose output 410 is the input tocommon-mode (as opposed to channel-specific) scaling system 820. Themagnitude calculation circuit 810 calculates the magnitude of thebaseband modulated signal 222 and generates a corresponding magnitudesignal 816. The magnitude calculation circuit 810 may be implemented inany suitable manner to determine the magnitude of samples of thebaseband modulated signal 222, such as a conventional circuit configuredto calculate the magnitude according to the following equation:M(n)=[I ²(n)+Q ²(n)]^(1/2)Where M(n) is the magnitude of the baseband modulated signal 222 for acomplex sample pair at sample n, I(n) is the in-phase component of thesignal for the complex sample pair I, and Q(n) is the quadraturecomponent of the signal for the complex sample pair I. The magnitudecalculation may be performed, however, according to any suitabletechnique or algorithm.

In the present embodiment as illustrated in FIG. 16, the magnitudesignal 816 is provided to the threshold circuit 812, which compares thecalculated magnitude to the magnitude threshold 412 and generates acorresponding comparison signal 818. The threshold circuit 812 maycomprise any suitable system for comparing the magnitude of the basebandmodulated signal 222 to the threshold. For example, the thresholdcircuit 812 may comprise a conventional comparator circuit orsubtraction circuit.

The magnitude threshold 412 may comprise any suitable value and/orsignal. For example, the threshold value may comprise a static value,such as one corresponding to the maximum power of the amplifier 216 or apower level slightly lower than the maximum power. Thus, the comparisonsignal 818 designates samples of the signal 222 corresponding to RFsignal values that would exceed the maximum power level of the amplifier216 or other suitable threshold. Alternatively, the magnitude threshold412 may be a dynamic value. The magnitude threshold 412 may be adjustedaccording to any suitable criteria. For example, the magnitude threshold412 may be calculated as a function of the signal power for the variouschannels and/or the amount of noise in the signal. Thus, if two channelsare operating at maximum power and two other channels are operating athalf the maximum power, the magnitude threshold 412 may be set at 75% ofthe maximum power. If the amount of noise in one or more channelsapproaches and/or exceeds a limit, such as the EVM threshold, themagnitude threshold 412 may be increased. Conversely, if the amount ofnoise is lower, the magnitude threshold 412 may be further decreased.Any suitable criteria or algorithm, however, may be used to select themagnitude threshold 412.

The communications system 100 may be configured to take advantage of thereduced peak-power requirements due to the peak-power reductioncomponent 212. For example, the communications system may be designed orreconfigured to use a lower-power amplifier to transmit signals. Inaddition, the communications system 100 may be configured to use theadditional power made available by the peak-power reduction component212 to improve the link between the transmitter 110 and the receiver 112and/or expand the coverage of the signal.

For example, the magnitude threshold 412 may be set at a selected levelto reduce the overall peak-power demand of the transmitter 110. Theaverage transmitted signal power may then be boosted so that thepeak-power transmitted by the system returns to its original level, butwith a higher average power of the transmitted signal. For example, ifthe threshold is originally set to reduce the peak-power requirement by3 dB, the transmitted power of the peak-reduced signal may be increasedby 3 dB to match the original peak-power. Thus, the same amplifier maybe used to transmit a higher average power signal, thereby enhancinglink quality. The magnitude threshold 412 may also be dynamicallychanged to reduce overall power consumption.

Reducing the level of the magnitude threshold 412 may raise the noiselevel in the transmitted signal. In many applications, however, thenoise in the transmitted signal is relatively low compared to theordinary noise level at the receiver, for example thermal noise. As aresult, because the noise level has only slightly increased while thepower of the transmitted signal has significantly increased, thesignal-to-noise ratio (SNR) at the receiver tends to improve.

In various environments, the reduction of the magnitude threshold 412 toboost the transmission power may be unacceptable, for example by causingthe SNR at the transmitter to contravene standards that may apply. Forexample, the current IEEE 802.16 standard requires the transmitter SNRto be no less than 19.6 dB. If the magnitude threshold 412 for thetransmitter 110 is reduced beyond a point, the induced noise fromgenerating the excursion may cause the SNR to drop below the 19.6 dBminimum, despite the improved overall quality of the link. In suchenvironments, the improved link quality may be implemented as an option.For example, the transmitter 110 and receiver 112 may be configured toinitially operate in accordance with the relevant standard. Thetransmitter 110 and receiver 112 may communicate to establish whetherthe other may operate using the improved quality link. If the unitsshare the ability to communicate with the improved quality link, thetransmitter 110 and receiver 112 may be reconfigured, either manually orautomatically, to reduce the magnitude threshold 412 to the lower leveland boost the respective transmission levels.

In one embodiment, the threshold circuit 812 monitors the EVM value foreach channel and adjusts the magnitude threshold 412 to minimize signalpeaks (i.e. maximize peak-reduction) while remaining within EVMspecifications. If the noise is low enough that the measured EVM valueis below the relevant limit, the threshold circuit 812 decreases themagnitude threshold 412. If the EVM magnitude approaches or exceeds therelevant limit, the threshold circuit increases the magnitude threshold412.

Referring again to FIG. 16 and continuing with the description of theimplementation details of the various exemplary embodiments, thecomparison signal 818 is provided to the waveform generator 814. Thewaveform generator 814 generates the excursion signal 410 according tothe comparison signal 818. The waveform generator 814 may be configuredin any suitable manner to generate the excursion signal 410, such as aconventional subtraction circuit to subtract the magnitude threshold 412value from the magnitude component of the baseband modulated signal 222.Another exemplary method for generating the excursion would employ theCORDIC algorithm. See, e.g., Ray Andraka, “A Survey of CORDIC Algorithmsfor FPGA-based Computers,” Proceedings of the 1998 ACM/SIGDA SixthInternational Symposium on Field Programmable Gate Arrays, Feb. 22-24,1998, Monterey, Calif., pp. 191-200. Preferred CORDIC algorithm usageinvolves a series of phase-rotation operations to rotate the originalsignal vector (i.e. sample) to an equivalent-magnitude zero-phasevector, while simultaneously performing conjugate phase rotationoperations on a vector initialized to zero-phase and magnitude equal tothe magnitude threshold 412; the excursion sample equals the differencebetween this resultant vector and the original complex vector if theoriginal signal magnitude is greater than the magnitude threshold 412,and equals zero otherwise. The operations of the threshold circuit 812and the waveform generator 814 may be performed by a single circuit orsystem, such as a subtraction circuit configured to perform thecomparison to the magnitude threshold 412 and generate the waveform bysubtracting the magnitude threshold 412 from the magnitude of thebaseband modulated signal 222. If the comparison signal 818 indicatesthat the magnitude signal 816 does not exceed the magnitude threshold412, the waveform generator 814 may generate a null signal. If thecomparison signal 818 indicates that the magnitude signal 816 exceedsthe magnitude threshold 412, the waveform generator 814 generates asignal having a magnitude corresponding to the difference between themagnitude of the baseband modulated signal 222 and the magnitudethreshold 412, and phase being identical to the baseband modulatedsignal. The resulting excursion signal may then be filtered, scaled, andsubtracted from a suitably delayed version of the baseband modulatedsignal 222 to reduce signal peaks.

In various embodiments, a common-mode scaling system 820, as shown inFIG. 16, may be provided and configured to adjust the magnitude of thegenerated (excursion) waveform so that the resulting scaled excursionsignal, after filtering, reduces peaks in the baseband modulated signal222 that initially exceed the magnitude threshold so that they equal aselected value, generally the magnitude threshold value. The common-modescaling system 820 receives the unscaled excursion signal 410 from thewaveform generator 814 and selectively adjusts the magnitude of theexcursion samples to generate the scaled excursion signal 516. Thesystem 820 may scale the excursion signal 410 according to any suitableprocess and may be implemented in any suitable manner. For example, thesystem 820 may be configured to selectively adjust the unscaledexcursion signal 410 such that the maximum magnitude of the peak-reducedsignal 224 does not exceed the selected magnitude threshold. Forexample, if the magnitude threshold 412 for a particular system is 1.8and the magnitude of the baseband modulated signal 222 is 4.0, thecommon mode scaling system 820 is suitably configured to scale the peakmagnitude of the corresponding sample generated by the peak powerreduction component 212, such as a scaled and filtered excursion signal552 (as shown in FIG. 14), to 2.2. In still another example, the commonmode scaling system may be configured to scale the excursion signalbased on the ratio of the peak magnitude of the unfiltered excursionsignal 410 to the peak magnitude of the filtered excursion signal 410B.As discussed above, this ensures that the scaled and filtered excursionpeak magnitude substantially matches the original excursion peakmagnitude. As can be appreciated, any implementation which achieves thedesired objective of adjusting the magnitude of the generated waveformso that the filtered excursion signal reduces the signal peak to adefined threshold level or below is within the scope of the presentinvention.

With reference to FIG. 10, an excursion event 2310 may include multiplepeak events 2312. The boundaries between the peak events 2312 may bedefined according to any suitable criteria. Peak events 2312 areseparated by a trough sample 2314, which may be defined as an excursionevent sample having higher magnitude samples on each side. A peak event2312 may be defined as a set of excursion samples for which themagnitude of immediately adjacent samples are either lower than themagnitude threshold 412 (at an excursion boundary) or higher than themagnitude of the trough between two peak-events). The common-modescaling system 820 may thus suitably apply a selected scaling value toevery sample of a particular peak event 2312, for example according tothe magnitude of the highest magnitude sample in the pre-filtered peakevent, the post-filtered peak event, or both. Thus, all of the samplesbetween two troughs 2314 (or between the beginning of the excursion 2316and the first trough 2314 or between the last trough 2314 and the end ofthe excursion 2318) are scaled using the same scaling factor, which issuitably selected according to the highest magnitude samples in thegroup of samples constituting the peak events 2312 of an excursion event2310.

Thus, in various embodiments, as illustrated, for example, by FIG. 15,peak parser 910 may be provided and configured in any suitable manner toidentify peaks in the incoming signal, such as via the magnitude signalfrom the magnitude calculation circuit 810. In one embodiment, the peakparser 910 comprises a peak detector 920 and a buffer 922. The peakdetector 920 identifies a peak in the incoming signal in any suitablemanner, such as by comparing the magnitudes of successive complex pairsin the incoming signal.

In the present embodiment, the peak detector 920 provides a signal tothe buffer 922 when a peak is detected in the incoming signal samples.The buffer 922 is suitably configured to temporarily store the incomingsignal while the peak detector 920 identifies the peaks in the incomingsignal. The buffer 922 may comprise any suitable storage element, suchas a FIFO buffer having an appropriate number of storage elements. Whena peak is detected, the buffer 922 suitably provides the relevant datato the waveform generator 912. In the present embodiment, the waveformgenerator 814 is configured to generate an unscaled waveform in responseto the detected peak in the incoming signal samples.

As shown in FIG. 17, the peak parser 910 may also be suitably configuredto route the individual peaks to different scaling systems forprocessing. For example, when a first peak is identified, the peakparser 910 suitably transmits the peak event samples to a first scalingsystem 820A, and the next peak event samples may be transmitted to asecond scaling system 820B, and the following peak event samples back tothe first scaling system 820A or an additional scaling system. Afterscaling, the scaled samples may be recombined to form a single scaledexcursion signal 516. Using different scaling systems 820A-B to processconsecutive peaks may advantageously reduce inter-peak processinginterference which may result from use of a single scaling system 820.Multiple scaling systems 820 may be implemented depending on processingsystem performance objectives.

In various embodiments, as shown illustratively in FIG. 14, the scaledexcursion signal 516 is provided to the excursion filter system 514 toeliminate unacceptable spectral energy, such as frequency componentsinduced by the excursion signal generator 512. The frequencies to befiltered may be selected according to any suitable criteria. Even thoughthe excursion signal resembles unchannelized broadband noise spanningapproximately 3× the bandwidth of the linear channelized signal, we mayconceptualize it as consisting of two distinct components: spectralenergy that cannot appear at the peak-reduction node 544 withoutviolating EVM specifications; and all other excursion spectral energy;the role of the excursion filter system is to separate these components,passing the latter while eliminating the former. The excursion signalthus “contains” the channelized excursion energy (allowable spectralenergy) as one component, and it is this component which is allowed topass (with suitable scaling) by the excursion filter system. That is,the excursion signal can be considered as being comprised of twodistinct components: (1) the allowable spectral energy; and (2) theunallowable spectral energy. However, there is no physical distinctionbetween the allowable and unallowable spectral energy components untilthe excursions filter system applies channel filtering, i.e., theexcursion is not channelized until filtering is applied. In the presentembodiment, spectral energy is attenuated or eliminated at anyfrequencies other than those approved by the applicable regulatoryspectral mask. In systems having multiple spectral energy levels acrossa particular signal passband, the excursion filter system 514 may beconfigured to adjust the relative spectral energy levels across thepassband to approximately match the in-band variations. For example, ifone portion of a channel's average power spectrum is 10 dB lower thanthe rest of the power spectrum, as might be the case when the channelconsists of adjacent sub-channels, the excursion filter system 514 mayintroduce a matching 10 dB relative attenuation of the excursionspectrum across the same frequency range.

The excursion filter system 514 may be configured in any suitable mannerto substantially filter the unwanted frequencies and transmit thedesired frequencies, or otherwise promote the transmission of desiredfrequencies and/or attenuate unwanted frequencies. For example, theexcursion filter system 514 is suitably configured to separate thescaled excursion signal 516 into individual frequency componentscorresponding to the input channels. The excursion filter system 514filters individual components of the excursion signal corresponding tobaseband modulated signal 222 to eliminate any unacceptable powerspectral energy. Alternatively, the excursion filter system 514 may beconfigured as a bandpass or bandstop filter to pass or attenuate powerspectral energy at selected frequencies, or otherwise configured toalter the distribution of power spectral energy over a defined frequencyrange. In addition, the excursion filter system 514 may comprisemultiple filter systems, such as a cascade of filters or a set ofparallel filters.

In the present exemplary embodiment, the excursion filter system 514comprises multiple parallel channel filters 518 whose outputs are summedtogether. Each channel filter 518 suitably comprises a conventionaldigital filter for reducing excursion signal power at selectedfrequencies corresponding to the particular channel. For example, eachchannel filter 518 may include a down-converter 520, a low pass filter522, a channel-specific gain-adjustment 540, and an up-converter 524,and each channel filter 518 suitably operates in a similar manner.Referring to FIGS. 14 and 18A-C, the down-converter 520 receives thescaled excursion signal 516, which exhibits a wide range of frequenciesf_(S) (FIG. 18A). The down-converter 520 shifts the frequency of theentire input spectrum to the left or right, such as by an amountsubstantially corresponding to the center/offset frequency f_(A) of therelevant channel. The low pass filter 522 filters input signals tosubstantially eliminate signal energy above a selected cutoff frequencyf_(C) and substantially transmit signals below the selected cutofffrequency (FIG. 18B). The up-converter 524 shifts the frequency of thefiltered signal to a higher frequency, such as to a selected frequencyor by a selected amount. In the present embodiment, the up-converter 524shifts the center frequency by an amount substantially corresponding tothe center frequency of the relevant channel, i.e. back to the originalcenter/offset frequency (FIG. 18C). Outputs 542 from the various channelfilters 518 are then combined into a composite signal 552 by a filteredsignal summer 550.

As shown schematically in FIG. 14, an exemplary down-converter 520 forthe present embodiment comprises a multiplier 526 and a complexconjugate generator 528. The complex conjugate generator 528 receivesthe relevant digital synthesizer signal 318 from the relevant digitalsynthesizer 314 and generates a complex conjugate signal 530corresponding to the complex conjugate of the digital synthesizer signal318. The multiplier 526 multiplies the complex conjugate signal 530 withthe scaled excursion signal 516. The resulting frequency-shifted signal536 is a substantially identical waveform as the scaled excursion signal516, but frequency-shifted by an amount substantially equal to thenegative of the channel's offset frequency.

In the present embodiment, the frequency-translated signal 536 isprovided to the low-pass filter 522. The low-pass filter 522 may beimplemented in any suitable manner and may be configured to use anysuitable cutoff frequency. For example, the low-pass filter may comprisea single filter, multiple parallel filters, or a cascade of filters. Inthe present embodiment, the low-pass filter 522 comprises a digitallow-pass filter, such as a finite impulse response filter, having acutoff frequency corresponding to one-half the approved bandwidth of therelevant channel. For example, if the approved channel frequency rangeis 20 MHz to 20.5 MHz, the cutoff frequency may be set at one-half ofthe 500 kHz bandwidth, or at 250 kHz. The digital low pass filter 522thus transmits a filtered signal 538 comprising the components of thedown-adjusted signal 536 that are below the cutoff frequency andattenuates spectral components above the cutoff frequency. The low passfilter 522 suitably comprises an approximately linear phase filter tominimize the amount of phase and/or magnitude error induced by thefilter.

In a communications system using subchannels within the various channelpassbands, such as an OFDMA environment, each channel filter 518 mayinclude one or more bandpass or bandstop filters for filtering unwantedfrequencies. For example, referring to FIG. 19, the various channels ofbaseband modulated signal 222 may include sub-channels at differentfrequencies within the channel, such as in an OFDMA system. Each suchchannel filter 518 suitably includes multiple bandpass filters or seriesof bandstop filters 1710 for each sub-channel configured to filterfrequencies other than the sub-channel frequency. This sub-channelfiltering may be preferentially implemented using the fast fouriertransform (FFT),

In addition, the gain of each sub-channel filter 1710 may be adjustableto control the magnitude of the particular sub-channel, for example tofacilitate adjustment of the relative sub-channel spectral energy levelsacross the passband to approximately match the in-band variations, or tocomply with sub-channel EVM constraints. For example, referring to FIG.20, the baseband modulated signal 222 may comprise multiple mainchannels 1810, each of which includes multiple sub-channels 1812. Eachsub-channel filter 1710 suitably operates as a magnitude adjustmentcircuit to adjust the gain for the sub-channel to reduce interferencebetween sub-channels, such as by adjusting the sub-channel filter 1710magnitudes according to the relative average signal power magnitudes ofthe corresponding sub-channel. Thus, the sub-channel filter 1710 mayprovide greater attenuation of the sub-channel excursion signal for alower magnitude sub-channel signal, which tends to reduce theinterference attributable to the higher energy levels in the adjacentsub-channels, and may be critical to comply with sub-channel EVMconstraints.

In the present exemplary embodiment involving frequency shifting shownin FIG. 14, the filtered channel signal 538 is transmitted to theup-converter 524 for conversion back to the original channel frequencyoffset. In the present embodiment, the frequency-converter 524 comprisesa multiplier 532 which multiplies the filtered signal 538 with thedigital synthesizer signal 318 from the digital synthesizer 314 toreturn the filtered signal 538 to the original channel frequency offset,and a phase-shifter 534 required to compensate for processing-induceddelay.

The signal processing system may also be configured to adjust themagnitude and/or phase of the filtered signal 538. Because the filteredexcursion is to be subtracted from the baseband modulated signal 222,the filtered excursion is suitably configured to exactly match theportion of the baseband modulated signal 222 that exceeds the threshold412. Channel filtering may alter its passband magnitude and phaserelative to the baseband modulated signal 222. Infinite-impulse response(IIR) filtering may be used to reduce the filter complexity relative tothat required using finite-impulse-response (FIR) filtering; however,IIR filtering introduces nonlinear phase distortion and passbandmagnitude ripple in the signal passband that can degrade peak-reduction,Further, the magnitude of the filtered signal 538 may be adjusted toconform to transmission requirements or other considerations.Consequently, the signal processing system may be configured using anequalizer to adjust the passband magnitude and/or phase of the filteredsignal 538 to reduce passband distortion in the channel filter. Theequalization function is suitably integrated into the low pass filtersystem 522, or may comprise a separate equalization circuit 566 forprocessing the filtered signal 538. The low pass filter 522 suitablycomprises an FIR or equalized-IIR low pass filter. Low pass filter 522is a single channel's LPF, whereas the impulse response of interest incomputing common-mode scaling is that of the entire excursion filtersystem 514.

Phase equalization causes the composite phase shift as a function of thefrequency for the cascade of the channel filter and the equalizer to beas close to linear as possible. The phase equalization function issuitably implemented as an all-pass filter (i.e. all magnitudes arepassed with unity magnitude) whose phase-shift-vs-frequencycharacteristic can be adjusted. The phase equalizer is suitablyconfigured to compensate for phase shifts induced by the low pass filter522 and/or any other sources of unwanted phase shifts. Magnitudeequalization addresses passband magnitude ripple distortion by adding acancellative passband magnitude ripple, such that the net ripple (i.e.product of the cascaded magnitude effects) is reduced.

In the present exemplary embodiment as shown schematically in FIG. 14,each individual channel filter 518 also includes a dedicated phasecorrection element 534 to compensate for the phase shift introduced byfrequency conversion operations and processing propagation delay. Thephase correction element 534 suitably adjusts the phase (in radians) ofthe filtered signal 538 according to the radian frequency (in rad/sec)of the digital synthesizer signal 318 from the digital synthesizer 314multiplied by the duration (in seconds) of the propagation delay throughthe channel filter 518. For example, the phase correction element 534may adjust the phase of the digital synthesizer signal 318 prior tousing it to up-convert the filtered excursion energy. Thischannel-specific phase shift assures that a channel filter 518 inputsinewave in the channel passband will exit from that channel filter withno change in magnitude or phase.

In an exemplary embodiment including frequency shifting, the resultingfrequency-converted, phase-adjusted scaled and filtered excursion 552comprises a waveform corresponding to the scaled excursion of thebaseband modulated signal 222 beyond the threshold magnitude. Due to thefiltering, the phase-adjusted filtered signal 552 only an acceptableamount of spectral energy outside the approved bandwidth.

One purpose of the present inventive concept is that the scaledexcursion signal 516 is provided to the excursion filter system 514 toremove any components in the scaled excursion signal 516 outside of theapproved channel bandwidths. In particular, the scaled excursion signal516 is provided to each down-converter 520, which translates the centerfrequency of the signal from each channel offset frequency to baseband.The frequency-translated signal 536 is then provided to the low-passfilter 522, which filters out frequencies above the cutoff frequency. Inthe present embodiment, the cutoff frequency corresponds to one half thebandwidth of the approved bandwidth. The filtered signal 538 is thenadjusted by the up-converter 524 to frequency-translate the signal tothe original channel offset frequency. The filtered signal, includingsub-channels within a particular passband or channel, may also beprocessed for phase and magnitude adjustment to compensate for changesinduced by the excursion signal generator 512 and the excursion filtersystem 514.

In a system using sub-channels, each channel filter 518 may adjust themagnitude of the various sub-channel filters according to the magnitudesof the sub-channels in the signal. Consequently, sub-channel signals inthe excursion signal having lower magnitudes are subjected to greaterattenuation than those having greater magnitudes. In a time divisionenvironment, each channel filter 518 may adjust the magnitude of thevarious channel filter gain-adjustments in a manner dependent on thetime slots for the excursion signal according to the magnitudes of thesignals in those time-slots in the baseband modulated signal 222. Thus,excursion channel time slots corresponding to signal channel time slotshaving lower energy magnitudes are subjected to greater attenuation thanexcursion channel time slots corresponding to signal channel time slotshaving greater energy magnitudes. Each channel filter 518 may also applya smoothing window to the filtered excursion signal generated by thatchannel filter.

The composite filtered signal 552 comprises a waveform corresponding tothe waveform of the excursion beyond the threshold in the basebandmodulated signal 222. By filtering the excursion signal, unwantedfrequency components, such as those attributable to spectral regrowth orother signal processing effects, may be eliminated from the compositefiltered excursion signal 552. When this composite filtered signal 552is subtracted from the delayed baseband modulated signal 222 by theexcursion reducer, the resulting peak-reduced signal 224 tends toexhibit maximum peak magnitudes that are essentially equal to themagnitude threshold and exhibit few or no unwanted frequency componentsintroduced by the peak-power reduction component 212. Consequently, thepeak-power of the signal decreases, facilitating use of a lower costamplifier 216 while satisfying all regulatory spectral constraints(masks) and minimizing distortion to the original signal.

In addition, the peak-reduction component 212 need not preciselydetermine the instant at which an excursion peak occurs, or the preciseamplitude and phase value of the peak, as is critical in manyalternative approaches. E.g., T. May and H. Rohling, “Reducing thePeak-To-Average Power Ratio in OFDM Radio Transmission Systems,” Proc.1998 Vehicular Tech. Conf., vol. 3, pp. 2474-78, May 18-21, 1998.Peak-reduction techniques that subtract a scaled and time-alignedversion of a constant band-limited pulse shape from the original signalare known to exhibit high sensitivity to errors in determining theprecise magnitude, phase and precise instant at which the peak occurs,forcing high over-sampling to mitigate this degradation, as described byM. Lampe and H. Rohling, “Reducing Out-of-Band Emissions Due toNonlinearities in OFDM Systems,” 49th IEEE Conference on VehicularTechnology, 16-20 May, 1999, pp. 2255-2259. The alternative methoddescribed herein completely eliminates this critical sensitivity byprocessing a multi-sample portion (i.e. peak-event) of the excursionwaveform; each individual peak event is scaled, filtered and subtractedfrom the baseband modulated signal 222 with corrections for delays andequalization. Further, the peak-power reduction component suitablyoperates in the same manner, regardless of the number of input signals.The substantial peak-reduction performance improvement using the newapproach is directly attributable to eliminating the prior art'slimitation of scaling a constant (band-limited) pulse shape; the highlyvariable shape of signal peaks demands generation of an optimalcancellation waveform (i.e. filtered and scaled peak-event) for eachindividual signal peak.

The composite filtered signal 552 may be provided to the excursionreducer 544 or subjected to further processing. Additional processingmay comprise any suitable processing, such as to improve the signal oradapt the signal to a particular environment. For example, the compositefiltered signal 552 may be processed using further peak-power reductionprocessing or filtering, such as via another peak-power reductioncomponent 212. The signal may exhibit slight variation in the maximummagnitude of its peaks due to filter response in the precedingpeak-power reduction processing, scaling misadjustments, or othersources. Repetitive peak-power reduction processing reduces suchvariation.

Referring to FIG. 14, the filtered signal 538 may also be furtherprocessed according to any desired criteria. For example, the filteredsignal 538 may be provided to a channel scaling/gain control element540, for example between the channel lowpass filter (LPF) filter 522 andthe up-converter 524. Such a channel scaling circuit may be used in theexcursion-reduction approach of the present invention as illustrated,for example, by FIG. 21.

In one embodiment, the channel gain control element 540 may adjust therelative signal energy for the multiple signals to control the amount ofin-band noise added to either the overall signal or any individualchannel. For example, the channel gain control element 540 may beresponsive to basestation control signals that adjust the transmissionpower for a particular channel, such as according to the estimatedattenuation between the transmitter 110 and the receiver 112.

In an alternative embodiment, the channel gain control element 540 mayadjust the magnitude of the filtered signal 538 to control the amount ofnoise added to the signal that may be caused by the peak-power reductioncomponent 212. For example, in cellular communications, the acceptableamount of noise that may be added to a particular channel is typicallyconstrained by error vector magnitude (EVM) specifications. Thepeak-power reduction component 212, however, may add noise to one ormore channels. For example, peak reduction may add noise to a lowerpower channel. To reduce the added noise, the channel gain controlelement 540 may adjust the amount of peak-power reduction applied to thelower power channel by adjusting the gain applied to the filtered signal538 for that channel.

FIG. 22 depicts a preferred embodiment of a functional architecture of apeak-reduction processing algorithm within the scope of the presentinvention and which may be further implemented according to the variousconfigurations described above. The composite multi-channel (MCS)baseband modulated signal 222 splits into two paths: the bottom pathcomputes the optimal peak-reduction cancellation waveform, whereas thetop path simply delays the original signal so that the peak-reductionsignal is properly time-aligned. The interpolator 502 is suitablyinterposed to expand the digital spectrum adequately so that thenonlinear spectral components created during excursion generation (anintrinsically nonlinear operation) remain adequately isolated from theoriginal signal spectrum. For purposes of the present description, it isassumed that the sample rate of the MCS waveform is sufficient tosatisfy the Nyquist-Shannon sampling theorem for the original basebandsignal. In this case, since the bandwidth of the excursion signal willbe at least three times that of the corresponding baseband signal, aninterpolator 502 must increase the sampling rate by at least a factor ofthree. Interpolator 502 combines the functions of increasing thesampling rate of the signal, as well as filtering off any spectral‘images’ created in this process. Occasionally, the sampling rate of theoriginal signal might be increased to facilitate sample rate conversion,in which case the additional explicit interpolator 502 might beunnecessary. It is critical however, that the sample rate at the inputto the excursion generator be at least three times that of theNyquist-Shannon sampling rate required to represent the baseband MCSsignal. The excursion signal, a complex baseband signal, is then splitinto two paths to facilitate scaling processing.

The output signal 504 of the interpolator is input to the excursiongenerator 512. The excursion signal 410 is generated by reference to amagnitude threshold level 412. The path from the excursion generatorleads to the peak parser 910, which is part of the common-mode scalingsystem 820. The peak parser 910 parses the set of contiguous complexsamples corresponding to each isolated excursion event into sets ofcomplex peak event samples as illustrated in FIG. 10. As noted, theminimum-magnitude (i.e. ‘trough’) sample point, for example, may bearbitrarily assigned to either the preceding or trailing peak event. Ina particular embodiment, the parsed peak events are used to compute anoptimal (real) scaling factor that is applied to each sample within eachpeak event. The embodiment of FIG. 22 may include scaling filter 2512and a peak scaling circuit 2514, as described more fully below withrespect to FIG. 28. The scaled sample stream may then be low-passfiltered and decimated (any required low-pass filtering is usuallyimplicit in a ‘decimator’) to reduce the sample rate back to the samplerate of the original MCS signal prior to applying the excursionfiltering; a lower sample rate significantly reduces the powerconsumption and complexity of the excursion filter implementation. Thedecimator 562, whether explicitly shown or not, is preferentially thelast operation in the scaling system. The scaled excursion signal 516 isprocessed by the excursion filter system 514. The excursion filterimposes spectral constraints on the scaled complex excursion samplestream. Constraints are also imposed on the excursion filtering processwith respect to error vector magnitude levels, residual distortion noiseand relative power levels of individual channel signals, as described inmore detail below with respect to the exemplary embodiments of FIGS. 21and 23. The scaled and filtered excursion signal 552 is then combinedwith a suitably delayed version of the baseband modulated signal 222 atexcursion reducer 544 to produce the peak-reduced digital basebandsignal 224.

Optimal peak reduction requires that each peak event be scaled by itsown unique scale factor. The optimal scale factor equals the ratio ofthe peak-magnitude of the raw (unfiltered) excursion to the peakmagnitude of the filtered excursion. It is clear from the discussion ofthe basic peak-reduction concept above that, if possible, simplysubtracting the unfiltered excursion waveform from the delayed signalwould result in a peak signal magnitude identically equal to themagnitude threshold 412 value. However, the excursion filtering requiredto satisfy spectral constraints distorts each peak event, with theresult that the peak of the difference between the delayed signal andthe filtered excursion will generally exceed the threshold. It is thusnecessary to determine a scaling factor which will restore the conditionthat the final peak-reduced signal peak magnitude substantially matchesthe threshold value. If the filter reduces the peak excursion magnitudeby a factor of two, then the excursion should be scaled by a factor oftwo to compensate for the filter's effective scaling. It is apparentthat the optimal scale factor is the ratio of the peak of the rawexcursion to that of the filtered excursion; it is less apparent how toeasily obtain the value of the peak magnitude of the filtered excursion.

Ideally, each distinct peak event would be passed through its ownexcursion filter system, the proper scale factor determined, these scalefactors then applied to each peak event in the composite excursionwaveform and the scaled peak events then passed through a finalexcursion filter system. However, the very long length of the excursionfilter system impulse response compared to the much shorter typicallength of a peak event poses implementation challenges. First,implementing a large number of such excursion filter systems addsundesirable implementation complexity. Second, the addition of this longprocessing step would require a corresponding delay for the original MCSsignal, and delay itself adds significant complexity. Resolution of thisdilemma requires scrutiny of the impulse response of the excursionfilter system.

The excursion filter system may, for example, include several (typically1-4) parallel finite-impulse response (FIR) bandpass filters, which maybe implemented using an architecture such as, for example, the onedepicted in FIG. 24. This type of architecture facilitates dynamictuning of the center frequencies for each of the N channels. Eachchannel filter may apply a unique spectral mask and each may beimplemented using either finite-impulse-response (FIR) orinfinite-impulse-response (IIR) filter architectures.

Regardless of the excursion filter system architecture employed, itsimpact is completely characterized by its impulse response, which willalways appear as a very long (complex) sequence. The magnitude of theexcursion filter system's impulse response will always exhibit anoscillatory variation in magnitude; it slowly increases, reaches a peak,and then slowly decays to zero. It is important to realize that therelatively few filter impulse response values located near the peakmagnitude values will approximately determine the peak magnitude of thefiltered peak event. Hence, the peak magnitude of the filtered excursionmay be computed using a very simple (approximation) FIR filter whoseimpulse response main lobe approximates that of the full-complexityexcursion filter system. FIG. 25 depicts the relationship between a longexcursion system filter (upper) and the approximate filter (lower) usedfor scaling. The upper filter impulse response curve of FIG. 25corresponds to the illustrated full-complexity multi-tap digital filterwhereas the lower curve corresponds to the illustrated approximationfilter having far fewer taps. The filter output at the instant when thepeak event magnitude peak is centered in either the full excursionfilter system or the simplified scaling filter is substantiallyidentical, since the peak event length is substantially the same as thescaling (approximation) filter length. It has been found that scalingfilters of very modest length yield nearly ideal peak event scaling. Themagnitude of the filtered peak event is preferably computed when itspeak magnitude point is aligned with the peak magnitude of the excursionimpulse response. The optimal scale factor substantially equals theratio of this magnitude value to that of the unfiltered peak event.

In the present exemplary embodiment, each parsed peak event is passedthrough a separate scaling filter, thereby determining the requiredscale factor with precision and low complexity. As discussed above, onlya few such scaling filters are required to substantially approximatelycompute the optimal scale factor, i.e., the ratio of the peak of the rawexcursion to the peak of the filtered excursion. The (real) scalefactors are then used to apply optimal scaling to each sample in eachpeak event as it emerges from the delay shown, for example, in FIG. 22.It is important to realize that this scaling filter concept, althoughdiscussed herein in the context of MCS, applies also to peak-reductionof OFDM and OFDMA waveforms, such as WiMAX signals, where many differentsub-channel modulation types and power levels characterize thetransmission, and EVM constraints must be satisfied. OFDMA transmissionsmay dynamically vary the sub-channel power levels and modulation ordersin response to environmental conditions, as do MCS channels, and at anypoint in time each channel has a unique maximum allowable value of noisepower based on the channel's dynamically-varying signal power andmodulation order (with attendant EVM value). The vector consisting ofchannel noise power maxima forms a passband energy mask which whentransformed into the time domain with an inverse-FFT yields acharacteristic filter impulse response analogous to both the full andsimplified excursion filter in FIG. 25. Optimal scale factors for eachpeak event across the OFDM symbol are determined using a similarprocedure as described for MCS waveforms. This processing is describedin FIG. 32. Knowledge of the modulation type used in each sub-channel,and the EVM specification associated with that modulation type, permitscalculation of a vector of allowed relative noise power levels for eachchannel. The absolute amount of peak-reduction noise in each channel isthen uniquely determined by these relative weightings and the actualmagnitude threshold value. FIG. 33 depicts the integrated OFDMpeak-reduction system architecture, in which the magnitude threshold isadaptively varied so that every OFDM channel has the maximum allowableamount of noise added to it by the peak-reduction processing. Thisassures the maximum possible amount of peak-reduction consistent withthe set of channel modulations and their associated EVM specifications.The scaled excursion waveform consisting of the concatenated scaled peakevents is filtered by forming the dot-product of the scaled excursionwaveform vector and the composite vector of passband and out-of-bandweights described above. Finally, the dot-product vector is transformedinto the time domain with an inverse-FFT, forming the filtered excursionwaveform vector; this is then time-aligned with the delayed OFDM symbolvector and subtracted from it to yield the peak-reduced OFDM symbol.

The apparent simplicity of this unique scaling approach obscures animportant assumption: that individual peak events may be scaledindependently of proximate peak events, i.e., a particular peak eventmay be scaled without regard to scaling of, for example, a peak eventwhich either precedes or trails the peak event under consideration.Research has determined that the described approach offers near-optimalpeak-reduction performance; more sophisticated scaling techniques do notyield appreciably better results. The following conclusions may thus bedrawn: (1) excursion filtering adequately smoothes the many abrupt gaindiscontinuities thus precluding the induced amplitude-modulation fromgenerating spectral mask violations and (2) the scaling error caused byproximate peak events is minimized because each target peak event iscentered in the scaling filter main lobe, attenuating the relativeimpact of all proximate peak events.

Before expanding the description beyond the exemplary architecture ofFIG. 22 it is important to understand how the error-vector magnitude(EVM) constraint interacts with the dynamically-varying relative powerlevels of the individual channel MCS signals. The EVM constraint andexcursion filter gain are inextricably intertwined. The EVMspecification ensures that standard link receivers are designed suchthat they will operate on transmitted waveforms which satisfy somedefined minimum quality level. The channel EVM specification is definedas the maximum tolerable ratio of noise to signal in each channel.Specifically, the EVM specification reads as

${{EVM}_{rms}\mspace{14mu}\%} \equiv {100\sqrt{\frac{\langle P_{N} \rangle}{\langle P_{S} \rangle}}}$Where P_(N) is the channel noise power and P_(s) is the channel signalpower. The channel-specific EVM specification constrains the total(composite) noise level in each transmission channel. Composite noiseconsists of several components including: (1) noise generated bypeak-reduction; (2) in-channel ‘noise’ corresponding to lineardistortion induced by frequency translation and amplification and (3)in-channel ‘noise’ induced by the power amplifier. In addition to thefact that the channel signal powers are varying dynamically in responseto estimated link propagation losses, EVM levels for each channel mayalso vary dynamically. Bandwidth-efficient (i.e. higher-order)modulations demand lower EVM levels for tolerable link degradation, andany link may switch between modulation types at any time. Since residualdistortion contributed by the amplifier and frequency conversion is alsotime-varying, and amplifier nonlinear noise is signal-dependent,ensuring that the EVM constraint is satisfied poses a major basestationdesign challenge.

Excursion generation, an intrinsically nonlinear operation, generatesnonlinear spectral energy that is approximately uniformly spread overthe linear signal bandwidth; the level of nonlinear energy can bedetermined entirely by a few maximum-strength channel signals. Thispresents difficulties with respect to the propagation of any weakchannel signals because the ratio of signal power to therelatively-fixed nonlinear noise level decreases as channel signal powerdecreases. At low channel signal power levels, the nonlinear noise insuch a weak channel bandwidth may violate the EVM constraint. Oneresponse to this problem, varying the gain in each excursion filterchannel to track the relative power in that channel has been previouslydescribed (See U.S. Patent Publication No. 2004/0266369). Simulationsdemonstrated such a simple gain control strategy prevented nonlinearnoise from degrading weak-channel EVM. However, this simple gain controlstrategy reduces channel gains much more than necessary to satisfy EVMconstraints, yielding sub-optimal peak-reduction performance; moreover,it is unable to adapt to variations in the other noise contributionscited above.

It is thus apparent that there is a difference between the degree ofgain control required to meet EVM constraints and that required toachieve optimal peak-reduction scaling. Optimal peak-reduction scalingrequires that peak-event-specific common-mode scaling be applied to eachpeak event sample whereas EVM protection requires channel-specific gaincontrol (rather than common-mode gain-control) responsive to the averagepower over many peak events. However, benefits within the scope of thepresent invention may be achieved using both the described common-modescaling and channel-specific scaling together or either alone. Moreover,the common-mode scaling of the present invention may be adaptivelyresponsive to a measured channel signal quality even in the absence ofchannel-specific gain control. For example, the common-mode scalingsystem may adjust peak event samples based on a feedback signalcomprised of a specified error vector magnitude value and/or a residualchannel or composite noise level.

The conceptual basis for the channel-specific gain control strategywithin the scope of the present invention is that the linear andnonlinear distortion noise induced by frequency conversion andamplification processing may be estimated and adaptively mitigatedduring subsequent processing, leaving some measurable amount of residualdistortion noise. Since this noise is independent of the peak-reductionprocessing noise, the composite noise power will be the root-mean-square(rms) sum of each of the independent noise processes. Both these noiseprocesses are only loosely correlated, and therefore combineapproximately in an rms manner. Once the rest of the channel noise isestimated, knowledge of the channel EVM limit permits computation of themaximum noise that may be added by peak-reduction processing. It is thenpossible to measure the short-term average noise actually being added bypeak-reduction, and use the ratio of these values to determine theproper gain for a particular channel. Recall that optimal peak-reductionrequires each channel gain to be unity. Thus when the measured channelnoise is less than required to satisfy the EVM specification, the gainshould default to a value of unity. However, when the peak-reductionnoise level exceeds its limit (as determined by the channel EVM limitand the estimated residual channel noise), a corrective gain equal tothe ratio of the noise limit to the measured noise must be applied. Ifthe measured peak-reduction rms channel noise is twice as high aspermitted, a gain of 0.5 must be applied to ensure EVM compliance.

The exemplary functional architecture discussed above with respect toFIG. 22 may be replaced with the exemplary embodiment of the inventionas depicted in FIG. 21, showing an exemplary excursion filter system 514in detail. However, the architecture of FIG. 22 is an equally validimplementation of various aspects of the present invention. A singlechannel filter 518 is shown in detail. Each channel filter 518 isfunctionally identical, although their parameter values will generallybe distinct.

The exemplary embodiment of FIG. 21 includes an excursion filter system514 which further includes an adaptive channel scaling (gain control)circuit 548 which compares the channel noise to a gain control thresholdbased on a relevant EVM standard. The EVM values are suitably computedon a channel-by-channel basis. Under various standards, the maximumchannel noise may be specified as having an EVM limit α, such as 17.5%or 12.5% of the root-mean-square (rms) power of the correspondingchannel signal of the baseband modulated signal 222. Referring to FIG.21, the average channel signal power may be computed, then scaled basedon the EVM specification for that channel, to obtain a limit on thetotal channel noise power. A transmitter system may employ any suitabletechniques and/or systems to reduce the noise induced by lineardistortions, such as linear equalization, as well as to reduce the otherdistortion noise, such as noise induced by nonlinearity intrinsic tohigh-power amplifiers, for example by linearization processing.Distortion mitigation techniques, however, may not eliminate all suchdistortion noise energy. The channel gain control circuit 548 may beconfigured to measure an amount of residual distortion noise energy ineach channel after application of distortion reduction processes, suchas after equalization and linearization processing. The channel gaincontrol circuit 548 may subtract this measured residual distortion noiseenergy from the EVM-permitted amount, which defines the permissiblenoise that may be added to each channel by the peak-reduction processingprocedure. If the rms power of the noise does not exceed the permissibleamount, the channel gain control circuit 548 may maintain unity gainresulting in the maximum peak reduction. If the rms power of the noiseexceeds the threshold, then the channel gain control circuit 548attenuates the filtered signal 538. The attenuation may be selectedaccording to any suitable criteria. In the present exemplary embodiment,the attenuation is selected to promote compliance with the relevantchannel EVM criterion. Thus, the desired gain G_(k) may be calculatedas:

$G_{k} \equiv \{ {{\begin{matrix}{{1{\_ if}{\_ P}_{xk}} \leq {AP}_{xk}} \\{\sqrt{\frac{{AP}_{xk}}{P_{xk}}}{\_ otherwise}}\end{matrix}\mspace{14mu}{AP}_{xk}} \equiv {{\alpha^{2}P_{sk}} - N_{k}}} $Where P_(xk), is the power of the signal exceeding the magnitudethreshold 412 for the kth channel, and P_(sk) is the signal power in thekth channel, α (which may include some margin) is the EVM limit for thekth channel, and N_(k) is the estimated residual distortion noise forthe kth channel. The maximum allowed amount of channel noise added tothe kth channel due to peak-reduction processing, AP_(xk), is computedby subtracting the estimated residual (linear and nonlinear) distortionnoise, N_(k), associated with frequency conversion and amplificationfrom this computed value of maximum acceptable (total) kth channelnoise, α²P_(sk). This equation corresponds, as an example, to thedesired-gain plot shown in FIG. 26.

AMR_(k), the ratio of the allowed added peak noise to the measured peaknoise in the kth channel is computed in the divider 2210. If this ratiois less than unity, there is no need to reduce the gain applied to thefiltered channel excursion signal. However, if this power ratio exceedsunity, then the gain must be reduced by a factor equal to thesquare-root of AMR_(k). This gain value, G_(k), 2216 is computed andapplied to a version of the filtered channel excursion signal at theoutput of the delay operator 2112. In addition, a modified version ofthis gain is fed back to the scaling system to ensure that peaks arescaled to reflect the new channel filter gain. The gain modification isrequired to avoid control loop stability problems encountered iffeedback gain values drop below a defined minimum. This minimum gainvalue, MinG, is sufficiently low that negligible peak scaling error isintroduced by limiting the lowest gain value fed back to the scalingsystem, as shown in FIG. 21.

The exemplary embodiment of FIG. 21 provides a method for ensuring thatthe long-term average value of EVM remains close to the value of α, butbecause the short-term EVM exhibits some random variation about thisvalue due to the structure of the signals—which vary dynamically, thelimit may be occasionally exceeded. Thus, a fixed nominal α value mustbe selected such that the upper reaches of the dynamic variation seldomexceed the specified limit. This implies that some peak-reductionpotential will remain unused if α is fixed. It is also difficult toempirically select an α target. The present invention thus includes anautomatic adaptive system that adjusts each channel α so that the EVMsubstantially matches the allowed limit. In this and similarembodiments, for example, a criteria is specified regarding tolerationof the EVM values exceeding a defined limit, for example by specifyingthe percentage of time such an excess EVM is acceptable. A determinationis then made regarding the extent to which the defined limit is actuallyexceeded. The target value of α is reduced if the tolerable limit isexceeded. On the other hand, the target value of α is increased if thetolerable limit is not reached. The difficulty of empirically selectinga target value for α is thus eliminated and the maximum amount of peakreduction achieved under all circumstances.

Referring again to FIG. 21, in this embodiment the baseband modulatedsignal 222 is provided to the delay element 510 and the interpolator502. A magnitude threshold 412 and an excursion generator 512, which maycomprise magnitude calculation circuit 810, threshold circuit 812, andwaveform generator 814, identifies portions of the interpolated basebandmodulated signal 504 beyond the magnitude threshold 412 and generates acorresponding unscaled excursion signal 410. The unscaled excursionsignal 410 comprises any suitable signal for reducing the peak in thebaseband modulated signal 222.

The unscaled excursion signal 410 is processed by the scaling system 820in such a manner that the maximum magnitude of signal peaks in thepeak-reduced signal 224 is approximately equal to the defined magnitudethreshold 412. The scaling system outputs the scaled excursion signal516 for further processing by the excursion filter system 514.

In the illustrative embodiment shown in FIG. 21, the complex samplestream from the excursion generator is optimally scaled, and thenfiltered by the excursion filter system 514 consisting of multipleparallel channel filters 518. Bandpass filtering is accomplished usingcascaded down-conversion, low-pass filtering, and then up-conversion;the indicated phase-shift is a common feature of this form of bandpassfilter implementation. P_(xk) is computed as the short-term average rmsnoise power added to a channel by peak-reduction processing. Asdiscussed, the maximum permissible value of the short-term average rmsnoise power is computed from the average channel signal power, the EVMtarget value (α_(k)) and the estimated residual (linear and nonlinear)distortion noise, N_(k), associated with frequency conversion andamplification. Note that, as individual channel gains vary over time,common-mode gain values within the scaling unit 820 must be adjusted tomaintain optimal peak event scaling.

FIGS. 27 and 27A illustrate the performance achievable using thepeak-reduction functional architecture shown in FIG. 21 with aparticularly challenging set of channel signal power levels: twoadjacent strong channels and two adjacent weak channels. FIGS. 27 and27A characterize simulated weak channel gain and EVM variation using thearchitecture described above. The top curve 2710 of FIG. 27 shows theraw EVM variation over time, the middle curve 2712 shows thecorresponding gain-controlled EVM and the bottom curve 2714 is thechannel gain multiplied by a factor of ten. Note that even though theweak channel's relative amplitude is only 0.1, the adaptive gain controlapproach described and claimed herein results in achievement of anaverage weak channel gain of approximately 0.6, and even duringintervals of peak EVM the weak channel gain is greater than 0.5. Thesedetailed computer simulation results verify that the present inventiveapproach and the described architecture ensures EVM compliance whileminimizing signal peak excursions. FIG. 27A confirms that this has beenachieved without violating the WCDMA spectral mask. In the absence ofadaptive gain control, the raw EVM 2710 exhibits±5% variation, whichwould require wasting 5% of the noise budget on margin. Note the greatlyreduced (five-fold) EVM variability 2712 using the inventive gaincontrol approach. The channel gain 2714 clearly shows the dynamicsinduced by the adaptive gain strategy described and claimed herein, andthe tightly-controlled resulting channel EVM clearly illustrates thebenefit of this gain-control strategy. FIG. 27A depicts the powerspectral density of the channel signals, particularly the two weakchannels, both before 2718 and after 2716 the adaptive gain controlstrategy has been applied; clearly there is negligible spectraldegradation (as far down as 80 dB) associated with the described gaincontrol strategy.

The gain control strategy described and claimed herein impacts thepeak-reduction performance in the following manner. Only those weakchannels which require EVM protection actually exhibit gain reductions,and then only the minimum required to satisfy EVM constraints; strongerchannels maintain their near-unity gains in order to maximize achievablepeak-reduction performance. Research demonstrates that the gain controlapproach of the present invention protects weak channels from EVMviolations while achieving near-optimal peak reduction.

The cited prior art references authored by Armstrong failed to recognizethe benefits of separately filtering the excursion and then subtractingthe result from the delayed original signal for all conventional OFDMsignals. The prior art recognized the need to interpolate the signalprior to clipping the OFDM signal, as well as the need to applyfiltering to reduce the out-of-band OFDM signal energy sufficiently tocomply with regulatory spectral masks. The prior art failed to realizethe importance of applying in-band dynamically adaptive filtering toprotect any relatively weak channel signals, and failed to recognize theopportunity to apply adaptive gain control to channels to ensure thatthey satisfy EVM specifications. The prior art also failed to grasp thebenefit of adaptive peak scaling in order to greatly improve peakreduction performance. The techniques and systems described and claimedherein thus provide numerous advantages over prior art techniques andsystems and are critical for ensuring EVM specifications are met foreach of the sub-channels within the OFDM signal, particularly as theydynamically vary in transmit strength. Of course, these advantages applyto MCS as well.

The algorithm/architecture described above may also be configured tomonitor the final peak reduced signal magnitude statistics, therebyadaptively adjusting the threshold value to optimize peak-reductionperformance. The industry-standard definition of a signal ‘peak’ is thatmagnitude value which is exceeded 0.01% of the time. The architecturedescribed above permits accurate measurement of signal statistics andconcomitant adjustment of the threshold value to minimize thisstatistical metric of signal peak.

The peak-reduction algorithm described above with reference to FIG. 21works very well in minimizing the PAR when all four channels are atmaximum power, and therefore achieves the benefit of reducing the costof the high-power amplifier (HPA) needed to support this embodiment ofthe invention. However, the life-cycle cost of a basestation is greatlyimpacted by the power consumption of those same HPAs. A furthermodification to the algorithm described with reference to FIG. 21wherein the threshold value is adaptively varied yields additionalbenefits in power consumption over the lifetime of the transmitter.Consider the situation in which all four channels are transmitting at apower level that is only 10% of their required peak transmission powerlevels. This situation actually occurs far more frequently than that inwhich all four channels are at maximum power. If the magnitude threshold412 is the same as that which minimizes PAR for all four channels atmaximum power, the peak-reduction processing algorithm described withreference to FIG. 21 will not have the desired effect of reshaping theCCDF of the signal, since the signal will only very rarely exceed thishigh magnitude threshold 412 level. If the PAR is to be minimized evenat this reduced power level, the threshold value must be adaptivelyreduced.

The present invention therefore includes in one embodiment, asillustrated in FIG. 23, an integrated control algorithm for both channelgains and magnitude threshold 412 driven by AMR_(k), the ratio ofallowed peak-reduction noise power to measured peak-reduction noisepower in each channel; the square-root of the channel AMR_(k) value isreferred to as that channel's ‘headroom,’ since it equals that channel'sestimated gain margin. Gain control loop stability considerationsestablish a minimum allowed value of channel gain, MinG. If driven atdefined time intervals, this algorithm is executed as follows:

Magnitude Threshold Control:

-   -   If any AMR_(k)<MinG, increase M    -   Else, If any AMR_(k)>1.0, decrease M    -   Else, maintain M at current value        This addition to the peak-reduction architecture and algorithm        described with respect to FIG. 21 results in the peak-reduction        architecture and algorithm depicted in FIG. 23. FIG. 23 is        identical to FIG. 21 with the addition of feedback from the        excursion filter system 514 to the threshold control system        2208, as shown by the dashed lines in FIG. 23. The structure and        operation of the peak-reduction architecture of FIG. 23 is such        that four parallel automatic-gain control (AGC) loops are driven        by channel-specific measurements, yet they result in feedback to        two serial common-mode operations (excursion generation and        peak-scaling) that impact all channels. The net result is a        unique ability to minimize peak-to-average-power-ratio (PAR) for        any combination of channel powers, and to dynamically adapt as        circumstances evolve. Since this processing yields a very        sharply defined peak magnitude under dynamically-varying channel        power levels, it is possible to dynamically control the maximum        supply voltage to the amplifier used to amplify this signal.        Since the power consumption of the amplifier is proportional to        its supply voltage, the sharply defined signal peak permits        substantial reduction in amplifier power consumption over all        operating conditions. In an alternative embodiment, a threshold        calculation circuit 2208 receives a feedback signal from the        output of the excursion filter system 514 and adjusts the        magnitude threshold 412 according to the magnitude of the output        signal. The magnitude threshold 412 may be adjusted based on the        peak-power reduction component 212 output according to any        suitable algorithm or process. For example, the threshold        calculation circuit 2208 may compare the output signal power or        the average output signal power over a selected time duration to        a selected level, such as the maximum power level of the        amplifier 216. If the output power level is substantially lower        than the selected level, the threshold calculation circuit 2208        may adjust the magnitude threshold 412 to a lower level. The        magnitude threshold 412 may also be scaled in response to other        criteria or output, for example in response to the output of the        peak-power reduction component 212.

The performance of the embodiment of the invention as illustrated inFIG. 23 is shown in FIGS. 27B and 27C, for a combination of four strongchannels, and in FIGS. 27D and 27E, for one weak channel and threestrong channels. FIG. 27B shows raw 2720 and peak-reduced 2722 CCDFplots for four strong channels. FIG. 27C shows 10× gain 2726 and EVM2724 variation versus time for four strong channels using EVM-basedexcursion channel filter gain control. FIG. 27D shows raw 2728 andpeak-reduced 2730 CCDF plots for one weak channel and three strongchannels. FIG. 27E shows EVM variation 2732 and 10× gain versus time forone weak channel 2736 and three strong channels 2734 using EVM-basedexcursion channel filter gain control. In both cases, EVM values for allfour channels quickly converge to the defined EVM target of 17%.

A further aspect of the inventive peak-reduction process targets therate of decline in the CCDF curves. An ideal peak-reducer would exhibita nearly vertical limit line implying the signal magnitude never exceedsthe limit. However, in reality the CCDF curves exhibit a slightflare-out that represents two primary mechanisms: 1) scaling errors and2) finite automatic gain control bandwidth and delay. The scaling errorsusually occur because of the influence on scaling of proximate peakevents, and because extremely long peak events can cause significantscale errors. Both flare-out mechanisms may be mitigated by simplypassing the peak-reduced waveform through a second application of thesame processing. FIG. 27F depicts an exemplary improved CCDF plotachieved using two cascaded peak-reduction operations. FIG. 27F shows anexemplary raw CCDF 2738, a peak-reduced CCDF 2740, and a peak-reducedCCDF 2742 that has undergone two cascaded peak-reduction operations.

The signal provided by the peak-power reduction component 212 may alsobe adjusted to compensate for changes in the magnitude of the signalincurred by the excursion filter system 514, for example by the channelscaling (gain control) circuits 548. For example, the common-modescaling system 820 may also be configured to adjust the common-modescaling factor to compensate for magnitude changes caused by the variouschannel circuits, such as channel gain adjustments that may be effectedby the channel scaling circuits 548. Common-mode scaling may thus beapplied to, for example, EVM control. Alternatively, the adjustment maybe performed by other components, such as a downstream amplifier, andthe common-mode scaling system 820 may adjust the signal according toany suitable criteria or information, such as feedback from theexcursion filter system 514, and/or approximations of changes in thesignal induced by other components such as the excursion filter system514.

The signal magnitude may be adjusted in any suitable manner andaccording to any suitable criteria. For example, in the presentexemplary embodiment, the common-mode scaling circuit 820 receives oneor more feedback signals from the channel scaling circuits 548. Thecommon mode scaling circuit 820 adjusts the common-mode scalingmagnitude based on the feedback signals. As is apparent, this feedbackapproach is consistent with the exemplary embodiments of the inventionas described in FIGS. 21 and 23.

In a preferred embodiment, the feedback signals comprise the scalingfactor, with a potentially-constrained minimum value, generated by eachchannel scaling circuit 548. For example, referring again to FIG. 21,the output of each comparison circuit 2212 may be provided to thecommon-mode scaling system 820. The common-mode scaling system 820 mayalso adjust the common-mode scaling factor according to any otherappropriate criteria, such as the known impulse responses of the variouschannel filters 518 that comprise the excursion filter system 514 inFIG. 24.

Note that in FIG. 21 the output of comparison circuits 2212 is shown asprovided directly to the scaling system 820. In an exemplary embodiment,the scaling system 820 may be configured to adjust the scaling accordingto an approximation of the changes incurred by excursion filter system514 or other components. However, the output of comparison circuits 2212may be provided directly to the scaling system 820 without any suchapproximation processing. In an embodiment including approximationprocessing, the approximation may be generated in any suitable manner,such as by an approximation filter having an impulse response similar tothat of the excursion filter system 514. For example, referring to FIGS.22 and 28, the scaling system 820 may comprise a scaling delay circuit2510, a scaling (approximation) filter 2512, and a peak scaling circuit2514. The incoming signal is provided to the scaling delay circuit 2510and the scaling (approximation) filter 2512. The scaling delay circuit2510 delays propagation of the signal while the scaling (approximation)filter 2512 and the peak scaling circuit 2514 process the signal. Thescaling (approximation) filter 2512 processes the signal to approximatethe effect of the excursion filter system 514 on the signal. The peakscaling circuit 2514 adjusts the scaling applied to the excursionsamples based on the effects indicated by the scaling (approximation)filter 2512.

The scaling (approximation) filter 2512 may be configured in anysuitable manner to approximate one or more effects of the excursionfilter system 514. The output sequence corresponding to each set ofexcursion samples may be computed for any excursion filter system 514.The output may comprise a smoothed version of the excursion waveform,sandwiched in between oscillations decaying in each direction of time.The oscillations are required to satisfy the spectral constraintsimposed by the excursion filter system 514. The scaling (approximation)filter 2512 may generate an accurate estimate of the smoothed excursionitself, without the oscillatory extensions, and the peak of the filteredexcursion or peak event determined. In one embodiment, the approximationfilter 2512 determines the scaling for each set of excursion samples asthe ratio of the peak magnitude of the input (unfiltered) peak event tothe maximum magnitude of the filtered peak event, which encourages thepeak-adjusted output signal maximum peaks to closely match the definedmagnitude threshold 412.

In the present embodiment, the scaling (approximation) filter reflectsthe effects of the various channel filters 518 and/or other componentscomprising the excursion filter system 514. For example, theapproximation filter may comprise simplified versions of each of the lowpass filters and their related components. Referring to FIGS. 14 and 28,each low pass filter 522 may comprise a multi-tap digital filter. Tomeet spectral requirements, the low pass filter 522 may be a relativelycomplex filter having dozens or hundreds of taps. Low pass filter 522 isa single channel's LPF, whereas the impulse response of interest is thatof the excursion filter system 514. The impulse response of theexcursion filter system 514 is substantially completely determined bythe impulse response of the lowpass filters 522, the channel offsetfrequencies 318 and the output of the channel scaling/gain controlelement 540. The approximation filter 2512 suitably comprises asimplified version of the impulse response of the excursion filtersystem 514, and may be implemented using substantially fewer taps, suchas five to ten taps. The approximation filter 2512 is suitablyconfigured to share the same tap values around the main lobe 2610 of theimpulse response 2612 of the excursion filter system 514, but onlyextends for a portion of the impulse response 2612 of the excursionfilter system 514. Although the output of the approximation filter 2512may not generate a signal compliant with the spectral requirements, thepeak magnitude of the approximation filter 2512 approximates the peakmagnitude of the excursion filter system 514.

Referring to FIG. 28, the peak scaling circuit 2514 receives theunscaled excursion 410 from the scaling (approximation) filter 2512 andadjusts the scaling applied to the original signal accordingly, forexample to counter the effects of the excursion filter system 514 on themagnitude of the excursion. In one embodiment, the peak scaling system2514 compares the signal from the approximation filter 2512 to theoriginal signal and adjusts the scaling accordingly. Thus, if themaximum sample magnitude of a peak event processed by the scaling(approximation) filter is 80% of the maximum sample magnitude of theunfiltered peak event, the peak scaling circuit 2514 may apply a scalingfactor of 1.25 to the original peak event samples to compensate for theattenuation induced by the scaling (approximation) filter 2512.

As is apparent for this and other embodiments, signals may be scaled,for example, to maximize peak reduction and remain within EVMspecifications. The channel filters 518 may attenuate individual channelsignals, reducing peak-reduction, if the noise in that channel isapproaching its EVM limits or other applicable signal quality criteria.In addition, the common-mode scaling circuit 820 may scale the samplesin each peak event to better match the magnitude threshold 412 bycompensating for changes in the excursion signal induced by theexcursion filter system 514. As is readily apparent, the embodiment ofthe invention illustrated by FIG. 28 is consistent with the exemplaryembodiments of the invention illustrated in FIGS. 21 and 23.

The channel gain control circuit 548 may also be configured to providetime slot scaling for time division multiple access (TDMA) or timedivision duplexing (TDD) signals, for example in conjunction with smooth“window” curves to transition between the nominal scalings used forsuccessive time slots. In particular, various time division schemes,such as those employed by burst CDMA and GSM, require the signal tosmoothly decrease in magnitude to substantially zero between time slots.Accordingly, the channel gain control circuit 548 may be configured toapply a time-varying gain to the filtered signal 538. For example,referring to FIG. 29, the channel gain control circuit 548 may apply aunity gain 850 to the filtered signal 538 for most of a time divisiontime slot 852, such as using a Blackman window or Hamming window. At theends 854 of the time slot 852, the gain is gradually adjusted betweenzero and unity such that the filtered signal 538 substantially smoothlyramps up from zero to unity gain 850, is held at unity gain 850 for mostof the time slot 852, then substantially smoothly ramps back down tozero near the end of the time slot 852. This smooth ramping reducesundesirable spectral artifacts associated with rapid signal magnitudevariations at each end of a time slot.

In one embodiment, the decay rate of the signal from the channel filter518 may be too slow to fully decay before the next time slot time.Accordingly, referring to FIG. 30, the channel filter 518 may beconfigured with additional filters 522 and a switching system 858 foreach channel. The additional filters 522 may comprise any number ofadditional filters 522 that may be required to filter the signal whileone or more other filters 522 allow their signals to decay. In thepresent embodiment, each channel includes two filters 522. The switchingsystem 858 switches the input and output for the channel between the twofilters 522 according to a time slot timing signal 860. Thus, a firsttime slot signal is filtered by the first filter 522A. At the end of thetime slot, the switching system 858 switches the signal input and outputto the second filter 522B. The second filter 522B handles the filteringduring the second time slot while the output of the first filter 522Adecays to zero. The switching system 858 switches back and forth betweenthe filters 522 so that each filter 522 is allowed to decay for theduration of a time slot before being used for the following time slot.

In various embodiments, the additional filters 522 and the switchingsystem 858 may be unnecessary, for example due to the operation of thetime scaling window and the channel gain control circuit 548 adjustingthe power of the filtered signal 538 in accordance with basestationcontrol signals, which may include maximum channel and time slot noiselimits derived from the modulation and EVM for that channel and timeslot. In particular, the nominal gain across each time slot may bevaried to match the average relative signal magnitudes in each timeslot, or to assure EVM compliance as previously described. For example,referring to FIG. 31, the energy in a first time slot TS₁ issignificantly higher than the energy in a second time slot TS₂. Thechannel filter 518 is suitably configured as a magnitude adjustmentcircuit to adjust the gain of the filtered signal 538 to a lowermagnitude during the second time slot TS₂. The filtered energy from ahigh-level time slot excursion is suitably attenuated sufficiently toreduce potential interference with a weaker signal in a subsequent timeslot. The channel gain control circuit 548 is configured to adjust theamplitude of the filtered signal 538, which includes the portion of thesignal that may be caused by the extended decay of the filter. As aresult, the portion of the filtered signal 538 attributable to theextended decay of the filter is attenuated, which tends to reduce itseffect on the intended signal.

Following processing by prior elements of the system, includingappropriate filtering, scaling and adjusting, the scaled and filteredexcursion signal 552 is provided to the excursion reducer 544, as shownin, for example, in FIG. 14. The excursion reducer 544 also receives thebaseband modulated signal 222 via the delay element 510. The delayelement 510 is configured to compensate for the propagation time of thesignal through the interpolator 502, excursion signal generator 512,scaling system 820, and excursion filter system 514. The excursionreducer 544 combines the baseband modulated signal 222 and the scaledand filtered excursion signal 542, for example, by subtracting thescaled and filtered excursion signal 542 from the delayed version of thebaseband modulated signal 222. The excursion reducer 544 generates apeak-reduced signal 224 having a maximum magnitude approximately equalto the magnitude threshold 412 and with few or no components outside theapproved bandwidth. The peak-reduced signal 224 is provided to the DAC214, which converts the peak-reduced signal 224 into an analog signal226 for amplification and transmission.

The communication system 100 may be used in various environments totransfer information, and may be adapted to the particular environmentor application. In various applications, the excursion filter system514, the excursion signal generator 512, or other elements of the systemmay be changed or optimized for the environment or application. Further,additional elements may be added to or removed from the communicationssystem 100 to facilitate or improve operation for the particularenvironment or application. For example, various applications orenvironments may utilize relatively low sampling rates compared to thecarrier frequencies. For example, under certain wireless communicationstandards, such as systems conforming to standards such as IEEE 802.11and 802.16 standards employing orthogonal frequency divisionmultiplexing (OFDM), sampling rates may approach the Nyquist limits forthe carrier frequencies. The peak-power reduction component 212 may beconfigured for improved operation in such low sampling rateapplications. In a further example application requiring increasedsampling frequency, the peak-power reduction component 212 may beadapted to reduce noise in the signals of interest. In one embodiment,the peak-power reduction component 212 is suitably configured to inhibitthe addition of noise to the signals of interest that may be caused bythe peak-power reduction process, such as intermodulation noisegenerated by the excursion signal generator 512. In particular, thesampling frequency of the baseband modulated signal 222 may besubstantially increased above the Nyquist sampling rate to inhibitaliasing of the excursion energy into the signal spectrum.

Referring to FIG. 32, an alternative exemplary embodiment of apeak-power reduction component 212 according to various aspects of thepresent invention comprises the delay element 510, the excursion signalgenerator 512, the excursion filter system 514, a sampling rate increasesystem 502, and a sampling rate reduction system 562. The sampling rateincrease (interpolator) system 502 increases the sampling rate of thebaseband modulated signal 222, while the sampling rate reduction system562 correspondingly reduces the sampling rate of the baseband modulatedsignal to its original rate. By increasing the sampling rate of thebaseband modulated signal 222 before generating the excursion signal,noise components caused by aliasing fall outside the spectra of thechannel signals, and may thus be filtered by the excursion filter system514. FIG. 32 is described in terms of an OFDMA application, but ofcourse the techniques described therein are equally applicable to anylow sampling rate applications or environment.

The sampling rate increase system 502 of FIG. 32 may comprise anysuitable system for increasing the sampling rate of the basebandmodulated signal 222. In the present embodiment, the sampling rateincrease system 502 consists of an interpolator configured to generateintermediate samples based on the original samples in the basebandmodulated signal 222. The interpolator may generate the intermediatesamples according to any suitable algorithm, such as a linearinterpolation. In addition, the interpolator may generate any suitablenumber of intermediate samples to achieve a desired increased frequency.In the present embodiment, the interpolator increases the sampling rateby a factor of about four.

Likewise, the sampling rate reduction system 562 of FIG. 32 may compriseany suitable system for decreasing the sampling rate of the signal fromthe excursion filter system 514 back to the original sampling rate. Inthe present embodiment, the sampling rate reduction system 562 includesa decimator configured to remove intermediate samples from the signal.In the present embodiment, the decimator decreases the sampling rate bya factor of about four to return the signal to the original samplingrate of the baseband modulated signal. It has been found that includingan interpolator and decimator in this manner to increase and decreasethe signal sampling rate, respectively, may advantageously reduce thepower required for the signal processing operations described andclaimed herein significantly, in the present embodiment by approximatelya factor of four. Power efficiencies may also be expected for otherinterpolator/decimator sampling rate scenarios. In a preferredembodiment, the decimation may occur between the scaling 820 and theexcursion filter system 514, in order to reduce the implementationcomplexity and power consumption of the excursion filter system 514.

In the OFDM environment, the excursion generator 512 in FIG. 32 isunderstood to incorporate the peak parsing and scaling functionspreviously described in detail. The excursion filter system 514 mayinclude an OFDM gain mask 564 configured to provide conformance to theregulatory and standard-based spectral constraints, but veryimportantly, the channel mask representing the maximum allowed channelnoise power (as determined by the signal power and channel EVMconstraint) previously described. The preferred embodiment of the gainmask operation 564 is a vector dot product of the frequency domainscaled excursion and the mask which results from the combination of theregulatory spectral constraints and channel noise power restrictions.The peak-power reduction component 212 may also perform additionalprocessing, such as substantially removing the DC component of thesignal, for example by subtracting the average of the in-phase andquadrature components of the signal from the samples corresponding tothe original samples.

The excursion filter system 514 may be further adapted for systems usingfast Fourier transforms (FFTs), such as an OFDMA communications systemunder the IEEE 802.16 standard. For example, referring to thealternative exemplary embodiment of FIG. 32, a peak-power reductioncomponent 212 according to various aspects of the present inventioncomprises the delay element 510, the excursion signal generator 512, theexcursion filter system 514, the sampling rate increase (interpolator)system 502, and the sampling rate reduction (decimator) system 562. Themodulator 210 is configured to generate a signal, such as an 802.16aOFDM symbol having cyclic prefix data. In the present embodiment, theexcursion filter system 514 includes an FFT filter system. To facilitatethe use of the FFTs, the sampling rate increase system 502 is suitablyconfigured to increase the sampling rate of the baseband modulatedsignal 222 such that the total number of samples in the OFDM vectorcorresponds to a power of two, such as by a factor of four. Similarly,the sampling rate reduction system 562 reduces the sampling rate of thebaseband modulated signal by the same amount.

In an alternative embodiment of the decimation and filtering systems ofFIG. 32, the sample rate reduction system may be eliminated and itsfunction implemented by the FFT filter system. By performing a largerFFT at the higher sample rate and discarding portions of the frequencydomain beyond the bandwidth of the baseband modulated signal, effectivedecimation prior to the gain mask operation may be realized. Of thesetwo alternatives, the preferred decimation and filtering embodiment mustbe chosen based on the processing resources available in the specificapplication.

Alternatively, the excursion waveform may only be generated for the rawOFDMA waveform, excluding the cyclic prefix, and the output of thepeak-reduction then modified to create a cyclic prefix corresponding tothe peak-reduction waveform itself, with the composite waveform thensubtracted from the delayed signal to accomplish peak reduction. Forexample, the excursion waveform may be generated without the cyclicprefix. After the peak-reduction process, for example after the summingof the various filtered excursions, a cyclic prefix may then begenerated based on the peak-reduction waveform. The prefix is thenattached to the front and back end of the transmitted signal.

The particular implementations shown and described are illustrative ofthe invention and its best mode and are not intended to otherwise limitthe scope of the present invention in any way. Indeed, for the sake ofbrevity, conventional manufacturing, connection, preparation, and otherfunctional aspects of the system may not be described in detail.Furthermore, the connecting lines shown in the various figures areintended to represent exemplary functional relationships and/or physicalcouplings between the various elements. Many alternative or additionalfunctional relationships or physical connections may be present in apractical system.

One such alternative embodiment simply uses a fixed common-mode scalingvalue for all excursion samples, where that scale value and anassociated magnitude threshold value are selected to optimizepeak-reduction for the case where all channels are near their maximumpower. The magnitude threshold value may then be selectively increasedto ensure EVM compliance when necessary as some channel power levelsdecrease. Even though this embodiment eliminates both the adaptivecommon-mode and channel-specific scaling, it provides substantialpeak-reduction benefit and is an application of our inventive conceptand architecture.

The present invention has been described above with reference topreferred embodiments. However, changes and modifications may be made tothe preferred embodiments without departing from the scope of thepresent invention. The order of processing steps described above withrespect to the method aspects of the present invention arerepresentative and the invention may be practiced in any sequence withinthe broad scope of the invention as described and claimed whichaccomplishes the stated objectives. These and other changes ormodifications are intended to be included within the scope of thepresent invention.

1. A signal processing system comprising: a distortion measuring systemconfigured to dynamically measure distortion in a signal, wherein thesignal comprises one or more channel signals transmitted via one or morechannels, a distortion determination system configured to dynamicallydetermine an allowable amount of distortion in at least one channelsignal, a distortion budgeting system configured to dynamically subtractmeasured distortion from allowable distortion to identify the maximumincremental distortion in at least one channel signal which may becreated by peak-reduction processing, and a peak-reduction processingsystem configured to reduce signal peaks in at least one channel signal,wherein the peak-reduction processing system creates no more than themaximum incremental distortion.
 2. The signal processing system of claim1, wherein the allowable amount of distortion is based on an errorvector magnitude specification.
 3. The signal processing system of claim1, wherein the system for dynamically determining an allowable amount ofdistortion is configured to determine an amount of noise that may beadded to a channel signal without exceeding a limit.
 4. The signalprocessing system of claim 1, wherein the distortion is comprised ofresidual linear and nonlinear distortion.
 5. The signal processingsystem of claim 1, further configured to process signals selected fromthe group consisting of TDD, GSM, CDMA, WCDMA, TDMA, QFDM, and OFDMAsignals, and signals formed as hybrids of this group.
 6. A method ofprocessing a signal, comprising: dynamically measuring distortion in atleast one channel signal of a signal comprised of one or more channelsignals transmitted via one or more channels, dynamically determining anallowable amount of distortion in at least one channel signal,dynamically subtracting measured distortion from allowable distortion toidentify the maximum incremental distortion in at least one channelsignal which may be created by peak-reduction processing, and reducingsignal peaks in at least one channel signal via peak-reductionprocessing, wherein the peak-reduction processing creates no more thanthe maximum incremental distortion.
 7. The method of claim 6, whereinthe allowable amount of distortion is based on an error vector magnitudespecification.
 8. The method of claim 6, wherein the step of dynamicallydetermining an allowable amount of distortion includes determining anamount of noise that may be added to a channel signal without exceedinga limit.
 9. The method of claim 6, wherein the distortion is comprisedof residual linear and nonlinear distortion.
 10. The method of claim 6,wherein the signal is selected from the group consisting of TDD, GSM,CDMA, WCDMA, TDMA, OFDM, and OFDMA signals, and signals formed ashybrids of this group.